Handling pipeline submissions across many compute units

ABSTRACT

One embodiment provides an apparatus comprising an interconnect fabric comprising one or more fabric switches, a plurality of memory interfaces coupled to the interconnect fabric to provide access to a plurality of memory devices, an input/output (IO) interface coupled to the interconnect fabric to provide access to IO devices, an array of multiprocessors coupled to the interconnect fabric, scheduling circuitry to distribute a plurality of thread groups across the array of multiprocessors, each thread group comprising a plurality of threads and each thread comprising a plurality of instructions to be executed by at least one of the multiprocessors, and a first multiprocessor of the array of multiprocessors to be assigned to process a first thread group comprising a first plurality of threads, the first multiprocessor comprising a plurality of parallel execution circuits.

CROSS-REFERENCE

This application is a continuation of co-pending U.S. patent applicationSer. No. 16/834,902, filed Mar. 30, 2020, which is a continuation ofU.S. patent application Ser. No. 16/446,946, filed Jun. 20, 2019, whichis a continuation of U.S. application Ser. No. 16/150,012, now issued asU.S. Pat. No. 10,497,087, which is a continuation of U.S. applicationSer. No. 15/493,233, now issued as U.S. Pat. No. 10,325,341, which isincorporated by reference in its entirety to the extent that it isconsistent with this disclosure.

FIELD

Embodiments relate generally to data processing and more particularly todata processing via a general-purpose graphics processing unit.

BACKGROUND OF THE DESCRIPTION

Current parallel graphics data processing includes systems and methodsdeveloped to perform specific operations on graphics data such as, forexample, linear interpolation, tessellation, rasterization, texturemapping, depth testing, etc. Traditionally, graphics processors usedfixed function computational units to process graphics data; however,more recently, portions of graphics processors have been madeprogrammable, enabling such processors to support a wider variety ofoperations for processing vertex and fragment data.

To further increase performance, graphics processors typically implementprocessing techniques such as pipelining that attempt to process, inparallel, as much graphics data as possible throughout the differentparts of the graphics pipeline. Parallel graphics processors with singleinstruction, multiple thread (SIMI′) architectures are designed tomaximize the amount of parallel processing in the graphics pipeline. Inan SIMT architecture, groups of parallel threads attempt to executeprogram instructions synchronously together as often as possible toincrease processing efficiency. A general overview of software andhardware for SIMT architectures can be found in Shane Cook, CUDAProgramming, Chapter 3, pages 37-51 (2013) and/or Nicholas Wilt, CUDAHandbook, A Comprehensive Guide to GPU Programming, Sections 2.6.2 to3.1.2 (June 2013).

BRIEF DESCRIPTION OF THE DRAWINGS

So that the manner in which the above recited features of the presentembodiments can be understood in detail, a more particular descriptionof the embodiments, briefly summarized above, may be had by reference toembodiments, some of which are illustrated in the appended drawings. Itis to be noted, however, that the appended drawings illustrate only,typical embodiments and are therefore not to be considered limiting ofits scope.

FIG. 1 is a block diagram illustrating a computer system configured toimplement one or more aspects of the embodiments described herein;

FIG. 2 illustrates a parallel processor according to an embodiment;

FIG. 3A is a block diagram of a partition unit, according to anembodiment;

FIG. 3B is a block diagram of a processing cluster, according to anembodiment;

FIG. 4A-4C are block diagrams of graphics multiprocessors, according toembodiments;

FIG. 5 illustrates an exemplary architecture in which a plurality ofGPUs is communicatively coupled to a plurality of multi-core processors;

FIG. 6 illustrates additional details for an interconnection between amulti-core processor and a graphics acceleration module in accordancewith one embodiment;

FIG. 7 illustrates another embodiment in which the acceleratorintegration circuit is integrated within the processor;

FIG. 8 illustrates an exemplary accelerator integration slice;

FIG. 9 illustrates additional details for one embodiment of a sharedmodel.

FIG. 10 illustrates a unified memory addressable via a common virtualmemory address space, according to an embodiment;

FIG. 11 is a conceptual diagram of a graphics processing pipeline,according to an embodiment;

FIG. 12 illustrates a subsystem for spawning threads within asingle-instruction multiple-data computation system, according to anembodiment;

FIG. 13 illustrates a subsystem for managing thread groups andsub-groups on an execution pipeline of a general-purpose graphicsprocessing unit, according to an embodiment;

FIG. 14 illustrates execution of thread sub-groups within a graphicsmultiprocessor, according to an embodiment;

FIG. 15 is a flow diagram of lop_ to launch thread sub-groups on agraphics multiprocessor, according to an embodiment;

FIG. 16 is a block diagram of a processing system, according to anembodiment;

FIG. 17 is a block diagram of a processor according to an embodiment;

FIG. 18 is a block diagram of a graphics processor, according to anembodiment;

FIG. 19 is a block diagram of a graphics processing engine of a graphicsprocessor in accordance with some embodiments;

FIG. 20 is a block diagram of a graphics processor provided by anadditional embodiment;

FIG. 21 illustrates thread execution logic including an array ofprocessing elements employed in some embodiments;

FIG. 22 is a block diagram illustrating a graphics processor instructionformats according to some embodiments;

FIG. 23 is a block diagram of a graphics processor according to anotherembodiment;

FIG. 24A-24B illustrate a graphics processor command format and commandsequence, according to some embodiments;

FIG. 25 illustrates exemplary graphics software architecture for a dataprocessing system according to some embodiments;

FIG. 26 is a block diagram illustrating an IP core development system,according to an embodiment;

FIG. 27 is a block diagram illustrating an exemplary system on a chipintegrated circuit, according to an embodiment;

FIG. 28 is a block diagram illustrating an additional graphicsprocessor, according to an embodiment; and

FIG. 29 is a block diagram illustrating an additional exemplary graphicsprocessor of a system on a chip integrated circuit, according to anembodiment.

DETAILED DESCRIPTION

In some embodiments, a graphics processing unit (GPU) is communicativelycoupled to host/processor cores to accelerate graphics operations,machine-learning operations, pattern analysis operations, and variousgeneral-purpose GPU (GPGPU) functions. The GPU may be communicativelycoupled to the host processor/cores over a bus or another interconnect(e.g., a high-speed interconnect such as PCIe or NVLink). In otherembodiments, the GPU may be integrated on the same package or chip asthe cores and communicatively coupled to the cores over an internalprocessor bus/interconnect (i.e., internal to the package or chip).Regardless of the manner in which the GPU is connected, the processorcores may allocate work to the GPU in the form of sequences ofcommands/instructions contained in a work descriptor. The GPU then usesdedicated circuitry/logic for efficiently processing thesecommands/instructions.

Parallel graphics processors with SIMT architectures are designed tomaximize the amount of parallel processing in the graphics pipeline. Inthe SIMT architecture, groups of parallel threads attempt to executeprogram instructions synchronously together as often as possible toincrease processing efficiency.

A graphics processing cluster array as described herein is capable ofexecuting potentially thousands of concurrent threads within multiplethread groups. In some instances, thread groups can be arranged as anarray of cooperating threads that concurrently execute the same programon an input data set to produce an output data set. Threads having thesame thread group ID can cooperate by sharing data with each other in amanner that depends on thread ID. For instance, data can be produced byone thread in a thread group and consumed by another thread in thethread group. Additionally, synchronization instructions can be insertedinto program code to ensure that that data to be consumed by a consumerthread has been produced by a producer thread before the consumer threadattempts to access the data. In instances where threads share access tocommon resources, it may be beneficial to execute all threads of thethread group within a single shader processor.

In the following description, numerous specific details are set forth toprovide a more thorough understanding. However, it will be apparent toone of skill in the art that the embodiments described herein may bepracticed without one or more of these specific details. In otherinstances, well-known features have not been described to avoidobscuring the details of the present embodiments.

System Overview

FIG. 1 is a block diagram illustrating a computing system 100 configuredto implement one or more aspects of the embodiments described herein.The computing system 100 includes a processing subsystem 101 having oneor more processor(s) 102 and a system memory 104 communicating via aninterconnection path that may include a memory hub 105. The memory hub105 may be a separate component within a chipset component or may beintegrated within the one or more processor(s) 102. The memory hub 105couples with an I/O subsystem 111 via a communication link 106. The I/Osubsystem 111 includes an I/O hub 107 that can enable the computingsystem 100 to receive input from one or more input device(s) 108.Additionally, the I/O hub 107 can enable a display controller, which maybe included in the one or more processor(s) 102, to provide outputs toone or more display device(s) 110A. In one embodiment the one or moredisplay device(s) 110A coupled with the I/O hub 107 can include a local,internal, or embedded display device.

In one embodiment the processing subsystem 101 includes one or moreparallel processor(s) 112 coupled to memory hub 105 via a bus or othercommunication link 113. The communication link 113 may be one of anynumber of standards-based communication link technologies or protocols,such as, but not limited to PCI Express, or may be a vendor specificcommunications interface or communications fabric. In one embodiment theone or more parallel processor(s) 112 form a computationally focusedparallel or vector processing system that an include a large number ofprocessing cores and/or processing clusters, such as a many integratedcore (MIC) processor. In one embodiment the one or more parallelprocessor(s) 112 form a graphics processing subsystem that can outputpixels to one of the one or more display device(s) 110A coupled via theI/O Hub 107. The one or more parallel processor(s) 112 can also includea display controller and display interface (not shown) to enable adirect connection to one or more display device(s) 110B.

Within the I/O subsystem 111, a system storage unit 114 can connect tothe I/O hub 107 to provide a storage mechanism for the computing system100. An I/O switch 116 can be used to provide an interface mechanism toenable connections between the I/O hub 107 and other components, such asa network adapter 118 and/or wireless network adaptor 119 that may beintegrated into the platform, and various other devices that can beadded via one or more add-in device(s) 120. The network adapter 118 canbe an Ethernet adaptor or another wired network adaptor. The wirelessnetwork adaptor 119 can include one or more of a Wi-Fi, Bluetooth, nearfield communication (NFC), or other network device that includes one ormore wireless radios.

The computing system 100 can include other components not explicitlyshown, including USB or other port connections, optical storage drives,video capture devices, and the like, may also be connected to the I/Ohub 107. Communication paths interconnecting the various components inFIG. 1 may be implemented using any suitable protocols, such as PCI(Peripheral Component Interconnect) based protocols (e.g., PCI-Express),or any other bus or point-to-point communication interfaces and/orprotocol(s), such as the NV-Link high-speed interconnect, orinterconnect protocols known in the art.

In one embodiment, the one or more parallel processor(s) 112 incorporatecircuitry optimized for graphics and video processing, including, forexample, video output circuitry, and constitutes a graphics processingunit (GPU). In another embodiment, the one or more parallel processor(s)112 incorporate circuitry optimized for general purpose processing,while preserving the underlying computational architecture, described ingreater detail herein. In yet another embodiment, components of thecomputing system 100 may be integrated with one or more other systemelements on a single integrated circuit. For example, the one or moreparallel processor(s), 112 memory hub 105, processor(s) 102, and I/O hub107 can be integrated into a system on chip (SoC) integrated circuit.Alternatively, the components of the computing system 100 can beintegrated into a single package to form a system in package (SIP)configuration. In one embodiment at least a portion of the components ofthe computing system 100 can be integrated into a multi-chip module(MCM), which can be interconnected with other multi-chip modules into amodular computing system.

It will be appreciated that the computing system 100 shown herein isillustrative and that variations and modifications are possible. Theconnection topology, including the number and arrangement of bridges,the number of processor(s) 102, and the number of parallel processor(s)112, may be modified as desired. For instance, in some embodiments,system memory 104 is connected to the processor(s) 102 directly ratherthan through a bridge, while other devices communicate with systemmemory 104 via the memory hub 105 and the processor(s) 102. In otheralternative topologies, the parallel processor(s) 112 are connected tothe I/O hub 107 or directly to one of the one or more processor(s) 102,rather than to the memory hub 105. In other embodiments, the I/O hub 107and memory hub 105 may be integrated into a single chip. Largeembodiments may include two or more sets of processor(s) 102 attachedvia multiple sockets, which can couple with two or more instances of theparallel processor(s) 112. Some of the particular components shownherein are optional and may not be included in all implementations ofthe computing system 100. For example, any number of add-in cards orperipherals may be supported, or some components may be eliminated.

FIG. 2 illustrates a parallel processor 200, according to an embodiment.The various components of the parallel processor 200 may be implementedusing one or more integrated circuit devices, such as programmableprocessors, application specific integrated circuits (ASICs), or fieldprogrammable gate arrays (FPGA). The illustrated parallel processor 200is a variant of the one or more parallel processor(s) 112 shown in FIG.1, according to an embodiment.

In one embodiment the parallel processor 200 includes a parallelprocessing unit 202. The parallel processing unit includes an I/O unit204 that enables communication with other devices, including otherinstances of the parallel processing unit 202. The I/O unit 204 may bedirectly connected to other devices. In one embodiment the I/O unit 204connects with other devices via the use of a hub or switch interface,such as memory hub 105. The connections between the memory hub 105 andthe I/O unit 204 form a communication link 113. Within the parallelprocessing unit 202, the I/O unit 204 connects with a host interface 206and a memory crossbar 216, where the host interface 206 receivescommands directed to performing processing operations and the memorycrossbar 216 receives commands directed to performing memory operations.

When the host interface 206 receives a command buffer via the I/O unit204, the host interface 206 can direct work operations to perform thosecommands to a front end 208. In one embodiment the front end 208 coupleswith a scheduler 210, which is configured to distribute commands orother work items to a processing cluster array 212. In one embodimentthe scheduler 210 ensures that the processing cluster array 212 isproperly configured and in a valid state before tasks are distributed tothe processing clusters of the processing cluster array 212.

The processing cluster array 212 can include up to “N” processingclusters (e.g., cluster 214A, cluster 214B, through cluster 214N). Eachcluster 214A-214N of the processing cluster array 212 is capable ofexecuting a large number (e.g., thousands) of concurrent threads, whereeach thread is an instance of a program.

In one embodiment, different clusters 214A-214N can be allocated forprocessing different types of programs or for performing different typesof computations. The scheduler 210 can allocate work to the clusters214A-214N of the processing cluster array 212 using various schedulingand/or work distribution algorithms, which may vary depending on theworkload arising for each type of program or computation. The schedulingcan be handled dynamically by the scheduler 210 or can be assisted inpart by compiler logic during compilation of program logic configuredfor execution by the processing cluster array 212.

The processing cluster array 212 can be configured to perform varioustypes of parallel processing operations. In one embodiment theprocessing cluster array 212 is configured to perform general-purposeparallel compute operations. For example, the processing cluster array212 can include logic to execute processing tasks including but notlimited to, linear and nonlinear data transforms, filtering of videoand/or audio data, and/or modeling operations (e.g., applying laws ofphysics to determine position, velocity and other attributes ofobjects).

In one embodiment the processing cluster array 212 is configured toperform parallel graphics processing operations. In embodiments in whichthe parallel processor 200 is configured to perform graphics processingoperations, the processing cluster array 212 can include additionallogic to support the execution of such graphics processing operations,including, but not limited to texture sampling logic to perform textureoperations, as well as tessellation logic and other vertex processinglogic. Additionally, the processing cluster array 212 can be configuredto execute graphics processing related shader programs such as, but notlimited to vertex shaders, tessellation shaders, geometry shaders, andpixel shaders. The parallel processing unit 202 can transfer data fromsystem memory via the I/O unit 204 for processing. During processing thetransferred data can be stored to on-chip memory (e.g., parallelprocessor memory 222) during processing, then written back to systemmemory.

In one embodiment, when the parallel processing unit 202 is used toperform graphics processing, the scheduler 210 can be configured todivide the processing workload into approximately equal sized tasks, tobetter enable distribution of the graphics processing operations tomultiple clusters 214A-214N of the processing cluster array 212. In someembodiments, portions of the processing cluster array 212 can beconfigured to perform different types of processing. For example, afirst portion may be configured to perform vertex shading and topologygeneration, a second portion may be configured to perform tessellationand geometry shading, and a third portion may be configured to performpixel shading or other screen space operations, to produce a renderedimage for display. Intermediate data produced by one or more of theclusters 214A-214N may be stored in buffers to allow the intermediatedata to be transmitted between clusters 214A-214N for furtherprocessing.

During operation, the processing cluster array 212 can receiveprocessing tasks to be executed via the scheduler 210, which receivescommands defining processing tasks from front end 208. For graphicsprocessing operations, processing tasks can include indices of data tobe processed, e.g., surface (patch) data, primitive data, vertex data,and/or pixel data, as well as state parameters and commands defining howthe data is to be processed (e.g., what program is to be executed). Thescheduler 210 may be configured to fetch the indices corresponding tothe tasks or may receive the indices from the front end 208. The frontend 208 can be configured to ensure the processing cluster array 212 isconfigured to a valid state before the workload specified by incomingcommand buffers (e.g., batch-buffers, push buffers, etc.) is initiated.

Each of the one or more instances of the parallel processing unit 202can couple with parallel processor memory 222. The parallel processormemory 222 can be accessed via the memory crossbar 216, which canreceive memory requests from the processing cluster array 212 as well asthe I/O unit 204. The memory crossbar 216 can access the parallelprocessor memory 222 via a memory interface 218. The memory interface218 can include multiple partition units (e.g., partition unit 220A,partition unit 220B, through partition unit 220N) that are each directlycoupled to a portion (e.g., memory unit) of parallel processor memory222. The number of partition units 220A-220N generally equals the numberof memory units, such that a first partition unit 220A has acorresponding first memory unit 224A, a second partition unit 220B has acorresponding memory unit 224B, and an Nth partition unit 220N has acorresponding Nth memory unit 224N. In other embodiments, the number ofpartition units 220A-220N may not equal the number of memory devices.

In various embodiments, the memory units 224A-224N can include varioustypes of memory devices, including dynamic random access memory (DRAM)or graphics random access memory, such as synchronous graphics randomaccess memory (SGRAM), including graphics double data rate (GDDR)memory. In one embodiment, the memory units 224A-224N may also include3D stacked memory, including but not limited to high bandwidth memory(HBM). Persons skilled in the art will appreciate that the specificimplementation of the memory units 224A-224N can vary, and can beselected from one of various conventional designs. Render targets, suchas frame buffers or texture maps may be stored across the memory units224A-224N, allowing partition units 220A-220N to write portions of eachrender target in parallel to efficiently use the available bandwidth ofparallel processor memory 222. In some embodiments, a local instance ofthe parallel processor memory 222 may be excluded in favor of a unifiedmemory design that utilizes system memory in conjunction with localcache memory.

In one embodiment, any one of the clusters 214A-214N of the processingcluster array 212 can process data to be written to any of the memoryunits 224A-224N within parallel processor memory 222. The memorycrossbar 216 can be configured to route the output of each cluster214A-214N to the input of any partition unit 220A-220N or to anothercluster 214A-214N for further processing. Each cluster 214A-214N cancommunicate with the memory interface 218 through the memory crossbar216 to read from or write to various external memory devices. In oneembodiment the memory crossbar 216 has a connection to the memoryinterface 218 to communicate with the I/O unit 204, as well as aconnection to a local instance of the parallel processor memory 222,enabling the processing units within the different processing clusters214A-214N to communicate with system memory or other memory that is notlocal to the parallel processing unit 202. In one embodiment the memorycrossbar 216 can use virtual channels to separate traffic streamsbetween the clusters 214A-214N and the partition units 220A-220N.

While a single instance of the parallel processing unit 202 isillustrated within the parallel processor 200, any number of instancesof the parallel processing unit 202 can be included. For example,multiple instances of the parallel processing unit 202 can be providedon a single add-in card, or multiple add-in cards can be interconnected.The different instances of the parallel processing unit 202 can beconfigured to inter-operate even if the different instances havedifferent numbers of processing cores, different amounts of localparallel processor memory, and/or other configuration differences. Forexample, in one embodiment some instances of the parallel processingunit 202 can include higher precision floating point units relative toother instances. Systems incorporating one or more instances of theparallel processing unit 202 or the parallel processor 200 can beimplemented in a variety of configurations and form factors, includingbut not limited to desktop, laptop, or handheld personal computers,servers, workstations, game consoles, and/or embedded systems.

FIG. 3A is a block diagram of a partition unit 320, according to anembodiment. In one embodiment the partition unit 320 is an instance ofone of the partition units 220A-220N of FIG. 2. As illustrated, thepartition unit 320 includes an L2 cache 322, a frame buffer interface324, and a ROP 326 (raster operations unit). The L2 cache 322 is aread/write cache that is configured to perform load and store operationsreceived from the memory crossbar 216 and ROP 326. Read misses andurgent write-back requests are output by L2 cache 322 to frame bufferinterface 324 for processing. Dirty updates can also be sent to theframe buffer via the frame buffer interface 324 for opportunisticprocessing. In one embodiment the frame buffer interface 324 interfaceswith one of the memory units in parallel processor memory, such as thememory units 224A-224N of FIG. 2 (e.g., within parallel processor memory222).

In graphics applications, the ROP 326 is a processing unit that performsraster operations, such as stencil, z test, blending, and the like, andoutputs pixel data as processed graphics data for storage in graphicsmemory. In some embodiments, ROP 326 may be configured to compress z orcolor data that is written to memory and decompress z or color data thatis read from memory. In some embodiments, the ROP 326 is included withineach processing cluster (e.g., cluster 214A-214N of FIG. 2) instead ofwithin the partition unit 320. In such embodiment, read and writerequests for pixel data are transmitted over the memory crossbar 216instead of pixel fragment data.

The processed graphics data may be displayed on display device, such asone of the one or more display device(s) 110 of FIG. 1, routed forfurther processing by the processor(s) 102, or routed for furtherprocessing by one of the processing entities within the parallelprocessor 200 of FIG. 2.

FIG. 3B is a block diagram of a processing cluster 314 within a parallelprocessing unit, according to an embodiment. In one embodiment theprocessing cluster is an instance of one of the processing clusters214A-214N of FIG. 2. The processing cluster 314 can be configured toexecute many threads in parallel, where the term “thread” refers to aninstance of a particular program executing on a particular set of inputdata. In some embodiments, single-instruction, multiple-data (SIMD)instruction issue techniques are used to support parallel execution of alarge number of threads without providing multiple independentinstruction units. In other embodiments, single-instruction,multiple-thread (SIMT) techniques are used to support parallel executionof a large number of generally synchronized threads, using a commoninstruction unit configured to issue instructions to a set of processingengines within each one of the processing clusters 314. Unlike a SIMDexecution regime, where all processing engines typically executeidentical instructions, SIMT execution allows different threads to morereadily follow divergent execution paths through a given thread program.Persons skilled in the art will understand that a SIMD processing regimerepresents a functional subset of a SIMT processing regime.

Operation of the processing cluster 314 can be controlled via a pipelinemanager 302 that distributes processing tasks to SIMT parallelprocessors. The pipeline manager 302 receives instructions from thescheduler 210 of FIG. 2 and manages execution of those instructions viaa graphics multiprocessor 304 and/or a texture unit 306. The illustratedgraphics multiprocessor 304 is an exemplary instance of an SIMT parallelprocessor. However, various types of SIMT parallel processors ofdiffering architectures may be included within the processing cluster314. One or more instances of the graphics multiprocessor 304 can beincluded within a processing cluster 314. The graphics multiprocessor304 can process data and a data crossbar 310 can be used to distributethe processed data to one of multiple possible destinations, includingother graphics multiprocessors and/or shader units. The pipeline manager302 can facilitate the distribution of processed data by specifyingdestinations for processed data to be distributed vis the data crossbar310.

Each graphics multiprocessor 304 within the processing cluster 314 caninclude an identical set of functional execution logic (e.g., arithmeticlogic units, load-store units, etc.), which may be pipelined, allowing anew instruction to be issued before a previous instruction has finished.Any combination of functional execution logic may be provided. In oneembodiment, the functional logic support a variety of operationsincluding integer and floating point arithmetic (e.g., addition andmultiplication), comparison operations, Boolean operations (AND, OR,XOR), bit-shifting, and computation of various algebraic functions(e.g., planar interpolation, trigonometric, exponential, and logarithmicfunctions, etc.); and the same functional-unit hardware can be leveragedto perform different operations.

The series of instructions transmitted to the processing cluster 314constitutes a thread, as previously defined herein, and the collectionof a certain number of concurrently executing threads across theparallel processing engines (not shown) within a graphics multiprocessor304 is referred to herein as a thread group. As used herein, a threadgroup refers to a group of threads concurrently executing the sameprogram on different input data, with one thread of the group beingassigned to a different processing engine within a graphicsmultiprocessor 304. A thread group may include fewer threads than thenumber of processing engines within the graphics multiprocessor 304, inwhich case some processing engines will be idle during cycles when thatthread group is being processed. A thread group may also include morethreads than the number of processing engines within the graphicsmultiprocessor 304, in which case processing will take place overconsecutive clock cycles. Each graphics multiprocessor 304 can supportup to G thread groups concurrently. Additionally, a plurality of relatedthread groups may be active (in different phases of execution) at thesame time within a graphics multiprocessor 304.

In one embodiment the graphics multiprocessor 304 includes an internalcache memory to perform load and store operations. In one embodiment,the graphics multiprocessor 304 can forego an internal cache and use acache memory (e.g., L1 cache 308) within the processing cluster 314.Each graphics multiprocessor 304 also has access to L2 caches within thepartition units (e.g., partition units 220A-220N of FIG. 2) that areshared among all processing clusters 314 and may be used to transferdata between threads. The graphics multiprocessor 304 may also accessoff-chip global memory, which can include one or more of local parallelprocessor memory and/or system memory. Any memory external to theparallel processing unit 202 may be used as global memory. Embodimentsin which the processing cluster 314 includes multiple instances of thegraphics multiprocessor 304 can share common instructions and data,which may be stored in the L1 cache 308.

Each processing cluster 314 may include an MMU 315 (memory managementunit) that is configured to map virtual addresses into physicaladdresses. In other embodiments, one or more instances of the MMU 315may reside within the memory interface 218 of FIG. 2. The MMU 315includes a set of page table entries (PTEs) used to map a virtualaddress to a physical address of a tile and optionally a cache lineindex. The MMU 315 may include address translation lookaside buffers(TLB) or caches that may reside within the graphics multiprocessor 304or the L1 cache or processing cluster 314. The physical address isprocessed to distribute surface data access locality to allow efficientrequest interleaving among partition units. The cache line index may beused to determine whether or not a request for a cache line is a hit ormiss.

In graphics and computing applications, a processing cluster 314 may beconfigured such that each graphics multiprocessor 304 is coupled to atexture unit 306 for performing texture mapping operations, e.g.,determining texture sample positions, reading texture data, andfiltering the texture data. Texture data is read from an internaltexture L1 cache (not shown) or in some embodiments from the L1 cachewithin graphics multiprocessor 304 and is fetched from an L2 cache,local parallel processor memory, or system memory, as needed. Eachgraphics multiprocessor 304 outputs processed tasks to the data crossbar310 to provide the processed task to another processing cluster 314 forfurther processing or to store the processed task in an L2 cache, localparallel processor memory, or system memory via the memory crossbar 216.A preROP 312 (pre-raster operations unit) is configured to receive datafrom graphics multiprocessor 304, direct data to ROP units, which may belocated with partition units as described herein (e.g., partition units220A-220N of FIG. 2). The preROP 312 unit can perform optimizations forcolor blending, organize pixel color data, and perform addresstranslations.

It will be appreciated that the core architecture described herein isillustrative and that variations and modifications are possible. Anynumber of processing units, e.g., graphics multiprocessor 304, textureunits 306, preROPs 312, etc., may be included within a processingcluster 314. Further, while only one processing cluster 314 is shown, aparallel processing unit as described herein may include any number ofinstances of the processing cluster 314. In one embodiment, eachprocessing cluster 314 can be configured to operate independently ofother processing clusters 314 using separate and distinct processingunits, L1 caches, etc.

FIG. 4A-C illustrate graphics multiprocessors, according to embodiments.The illustrated graphics multiprocessors 400, 425, 450 are variants ofthe graphics multiprocessor 304 of FIG. 3. The illustrated graphicsmultiprocessors 400, 425, 450 can be configured as a streamingmultiprocessor (SM) capable of simultaneous execution of a large numberof execution threads.

FIG. 4A shows a graphics multiprocessor 400, according to oneembodiment. In such embodiment the graphics multiprocessor 400 coupleswith the pipeline manager 302 of the processing cluster 314 of FIG. 3.The graphics multiprocessor 400 has an execution pipeline including butnot limited to an instruction cache 402, an instruction unit 404, anaddress mapping unit 406, a register file 408, one or more generalpurpose graphics processing unit (GPGPU) cores 412, and one or moreload/store units 416. The GPGPU cores 412 and load/store units 416 arecoupled with cache memory 420 and shared memory 422 via a memory andcache interconnect 418.

In one embodiment, the instruction cache 402 receives a stream ofinstructions to execute from the pipeline manager 302 of FIG. 3. Theinstructions are cached in the instruction cache 402 and dispatched forexecution by the instruction unit 404. The instruction unit 404 candispatch instructions as thread groups (e.g., warps), with each threadof the thread group assigned to a different execution unit within GPGPUcore 412. An instruction can access any of a local, shared, or globaladdress space by specifying an address within a unified address space.The address mapping unit 406 can be used to translate addresses in theunified address space into a distinct memory address that can beaccessed by the load/store units 416.

The register file 408 provides a set of registers for the functionalunits of the graphics multiprocessor 400. The register file 408 providestemporary storage for operands connected to the data paths of thefunctional units (e.g., GPGPU cores 412, load/store units 416) of thegraphics multiprocessor 400. In one embodiment, the register file 408 isdivided between each of the functional units such that each functionalunit is allocated a dedicated portion of the register file 408. In oneembodiment, the register file 408 is divided between the different warpsbeing executed by the graphics multiprocessor 400.

The GPGPU cores 412 can each include floating point units (FPUs) and/orinteger arithmetic logic units (ALUs) that are used to executeinstructions of the graphics multiprocessor 400. The GPGPU cores 412 canbe similar in architecture or can differ in architecture, according toembodiments. For example, in one embodiment a first portion of the GPGPUcores 412 include a single precision FPU and an integer ALU while asecond portion of the GPGPU cores include a double precision FPU. In oneembodiment the FPUs can implement the IEEE 754-2008 standard forfloating point arithmetic or enable variable precision floating pointarithmetic. The graphics multiprocessor 400 can additionally include oneor more fixed function or special function units to perform specificfunctions such as copy rectangle or pixel blending operations. In oneembodiment one or more of the GPGPU cores can also include fixed orspecial function logic,

The memory and cache interconnect 418 is an interconnect network thatconnects each of the functional units of the graphics multiprocessor 400to the register file 408 and to the shared memory 422. In oneembodiment, the memory and cache interconnect 418 is a crossbarinterconnect that allows the load/store unit 416 to implement load andstore operations between the shared memory 422 and the register file408. In one embodiment the shared memory 422 can be used to enablecommunication between threads that execute on the functional units. Thecache memory 420 can be used as a data cache for example, to cachetexture data communicated between the functional units and the textureunit 306 of FIG. 3.

FIG. 4B shows a graphics multiprocessor 425 according to an additionalembodiment. The graphics multiprocessor 425 includes multiple additionalinstances of execution resource units relative to the graphicsmultiprocessor 400 of FIG. 4A. For example, the graphics multiprocessor425 can include multiple instances of the instruction unit 432A-432B,register file 434A-434B, and texture unit(s) 444A-444B. The graphicsmultiprocessor 425 also includes multiple sets of graphics or computeexecution units (e.g., GPGPU Core 436A-436B, GPGPU core 437A-437B, GPGPUcore 438A-438B) and multiple sets of load/store units 440A-440B. In oneembodiment the execution resource units have a common instruction cache430, texture and/or data cache memory 442, and shared memory 446. Thevarious components can communicate via an interconnect fabric 427. Inone embodiment the interconnect fabric 427 includes one or more crossbarswitches to enable communication between the various components of thegraphics multiprocessor 425.

FIG. 4C shows a graphics multiprocessor 450 according to an additionalembodiment. The graphics processor includes multiple sets of executionresources 456A-D, where each set of execution resource includes multipleinstruction units, register files, GPGPU cores, and load store units, asillustrated in FIG. 4A-4B. The execution resources 456A-D can work inconcert with texture unit(s) 460A-D for texture operations, whilesharing an instruction cache 454, and shared memory 462. In oneembodiment the execution resources 456A-D can share an instruction cache454 and shared memory 462, as well as multiple instances of a textureand/or data cache memory 458A-458B. The various components cancommunicate via an interconnect fabric 452 similar to the interconnectfabric 427 of FIG. 4B.

Persons skilled in the art will understand that the architecturedescribed in FIGS. 1, 2, 3A-3B, and 4A-4C are descriptive and notlimiting as to the scope of the present embodiments. Thus, thetechniques described herein may be implemented on any properlyconfigured processing unit, including, without limitation, one or moremobile application processors, one or more desktop or server centralprocessing units (CPUs) including multi-core CPUs, one or more parallelprocessing units, such as the parallel processing unit 202 of FIG. 2, aswell as one or more graphics processors or special purpose processingunits, without departure from the scope of the embodiments describedherein.

In some embodiments a parallel processor or GPGPU as described herein iscommunicatively coupled to host/processor cores to accelerate graphicsoperations, machine-learning operations, pattern analysis operations,and various general-purpose GPU (GPGPU) functions. The GPU may becommunicatively coupled to the host processor/cores over a bus or otherinterconnect (e.g., a high-speed interconnect such as PCIe or NVLink).In other embodiments, the GPU may be integrated on the same package orchip as the cores and communicatively coupled to the cores over aninternal processor bus/interconnect (i.e., internal to the package orchip). Regardless of the manner in which the GPU is connected, theprocessor cores may allocate work to the GPU in the form of sequences ofcommands/instructions contained in a work descriptor. The GPU then usesdedicated circuitry/logic for efficiently processing thesecommands/instructions.

Techniques for GPU to Host Processor Interconnection

FIG. 5 illustrates an exemplary architecture in which a plurality ofGPUs 510-1313 are communicatively coupled to a plurality of multi-coreprocessors 505-506 over high-speed links 540-543 (e.g., buses,point-to-point interconnects, etc.). In one embodiment, the high-speedlinks 540-543 support a communication throughput of 4 GB/s, 30 GB/s, 80GB/s or higher, depending on the implementation. Various interconnectprotocols may be used including, but not limited to, PCIe 4.0 or 5.0 andNVLink 2.0. However, the underlying principles of the invention are notlimited to any particular communication protocol or throughput.

In addition, in one embodiment, two or more of the GPUs 510-513 areinterconnected over high speed links 544-545, which may be implementedusing the same or different protocols/links than those used forhigh-speed links 540-543. Similarly, two or more of the multi-coreprocessors 505-506 may be connected over high speed links 535 which maybe symmetric multi-processor (SMP) buses operating at 20 GB/s, 30 GB/s,120 GB/s or higher. Alternatively, all communication between the varioussystem components shown in FIG. 5 may be accomplished using the sameprotocols/links (e.g., over a common interconnection fabric). Asmentioned, however, the underlying principles of the invention are notlimited to any particular type of interconnect technology.

In one embodiment, each multi-core processor 505-506 is communicativelycoupled to a processor memory 501-502, via memory interconnects 530-531,respectively, and each GPU 510-513 is communicatively coupled to GPUmemory 520-523 over GPU memory interconnects 550-553, respectively. Thememory interconnects 530-531 and 550-553 may utilize the same ordifferent memory access technologies. By way of example, and notlimitation, the processor memories 501-502 and GPU memories 520-523 maybe volatile memories such as dynamic random access memories (DRAMs)(including stacked DRAMs), Graphics DDR SDRAM (GDDR) (e.g., GDDR5,GDDR6), or High Bandwidth Memory (HBM) and/or may be non-volatilememories such as 3D XPoint or Nano-Ram. In one embodiment, some portionof the memories may be volatile memory and another portion may benon-volatile memory (e.g., using a two-level memory (2LM) hierarchy).

As described below, although the various processors 505-506 and GPUs510-513 may be physically coupled to a particular memory 501-502,520-523, respectively, a unified memory architecture may be implementedin which the same virtual system address space (also referred to as the“effective address” space) is distributed among all of the variousphysical memories. For example, processor memories 501-502 may eachcomprise 64 GB of the system memory address space and GPU memories520-523 may each comprise 32 GB of the system memory address space(resulting in a total of 256 GB addressable memory in this example).

FIG. 6 illustrates additional details for an interconnection between amulti-core processor 605 and a graphics acceleration module 616 inaccordance with one embodiment. The graphics acceleration module 616 mayinclude one or more GPU chips integrated on a line card which is coupledto the processor 605 via the high-speed link 540. Alternatively, thegraphics acceleration module 616 may be integrated on the same packageor chip as the processor 605.

The illustrated processor 605 includes a plurality of cores 610-613,each with a translation lookaside buffer 620-623 and one or more caches631. The cores may include various other components for executinginstructions and processing data which are not illustrated to avoidobscuring the underlying principles of the invention (e.g., instructionfetch units, branch prediction units, decoders, execution units, reorderbuffers, etc.). The caches 631 may comprise level 1 (L1) and level 2(L2) caches. In addition, one or more shared caches 626 may be includedin the caching hierarchy and shared by sets of the cores 610-613. Forexample, one embodiment of the processor 605 includes 24 cores, eachwith its own L1 cache, twelve shared L2 caches, and twelve shared L3caches. In this embodiment, one of the L2 and L3 caches are shared bytwo adjacent cores. The processor 605 and the graphics accelerationmodule 616 connect with system memory 611, which may include processormemories 501-502

Coherency is maintained for data and instructions stored in the variouscaches 630-633, 626 and system memory 611 via inter-core communicationover a coherence bus 620. For example, each cache may have cachecoherency logic/circuitry associated therewith to communicate to overthe coherence bus 620 in response to detected reads or writes toparticular cache lines. In one implementation, a cache snooping protocolis implemented over the coherence bus 620 to snoop cache accesses. Cachesnooping/coherency techniques are well understood by those of skill inthe art and will not be described in detail here to avoid obscuring theunderlying principles of the invention.

In one embodiment, a proxy circuit 630 communicatively couples thegraphics acceleration module 616 to the coherence bus 620, allowing thegraphics acceleration module 616 to participate in the cache coherenceprotocol as a peer of the cores. In particular, an interface 635provides connectivity to the proxy circuit 630 over high-speed link 540(e.g., a PCIe bus, NVLink, etc.) and an interface 607 connects thegraphics acceleration module 616 to the link 540.

In one implementation, an accelerator integration circuit 606 providescache management, memory access, context management, and interruptmanagement services on behalf of a plurality of graphics processingengines 601, 602, N of the graphics acceleration module 616. Thegraphics processing engines 601, 602, N may each comprise a separategraphics processing unit (GPU). Alternatively, the graphics processingengines 601, 602, N may comprise different types of graphics processingengines within a GPU such as graphics execution units, media processingengines (e.g., video encoders/decoders), samplers, and blit engines. Inother words, the graphics acceleration module may be a GPU with aplurality of graphics processing engines 601-602, N or the graphicsprocessing engines 601-602, N may be individual GPUs integrated on acommon package, line card, or chip.

In one embodiment, the accelerator integration circuit 606 includes amemory management unit (MMU) 609 for performing various memorymanagement functions such as virtual-to-physical memory translations(also referred to as effective-to-real memory translations) and memoryaccess protocols for accessing system memory 611. The MMU 609 may alsoinclude a translation lookaside buffer (TLB) (not shown) for caching thevirtual/effective to physical/real address translations. In oneimplementation, a cache 608 stores commands and data for efficientaccess by the graphics processing engines 601-602, N. In one embodiment,the data stored in cache 608 and graphics memories 603-604, N is keptcoherent with the core caches 630-633, 626 and system memory 611. Asmentioned, this may be accomplished via proxy circuit 630 which takespart in the cache coherency mechanism on behalf of cache 608 andmemories 603-604, N (e.g., sending updates to the cache 608 related tomodifications/accesses of cache lines on processor caches 630-633, 626and receiving updates from the cache 608).

A set of registers 615 store context data for threads executed by thegraphics processing engines 601-602, N and a context management circuit618 manages the thread contexts. For example, the context managementcircuit 618 may perform save and restore operations to save and restorecontexts of the various threads during context switches (e.g., where afirst thread is saved and a second thread is stored so that the secondthread can be execute by a graphics processing engine). For example, ona context switch, the context management circuit 618 may store currentregister values to a designated region in memory (e.g., identified by acontext pointer). It may then restore the register values when returningto the context. In one embodiment, an interrupt management circuit 617receives and processes interrupts received from system devices.

In one implementation, virtual/effective addresses from a graphicsprocessing engine 601 are translated to real/physical addresses insystem memory 611 by the memory management unit 609. One embodiment ofthe accelerator integration circuit 606 supports multiple (e.g., 4, 8,16) graphics accelerator modules 616 and/or other accelerator devices.The graphics accelerator module 616 may be dedicated to a singleapplication executed on the processor 605 or may be shared betweenmultiple applications. In one embodiment, a virtualized graphicsexecution environment is presented in which the resources of thegraphics processing engines 601-602, N are shared with multipleapplications or virtual machines (VMs). The resources may be subdividedinto “slices” which are allocated to different VMs and/or applicationsbased on the processing requirements and priorities associated with theVMs and/or applications.

Thus, the accelerator integration circuit acts as a bridge to the systemfor the graphics acceleration module 616 and provides addresstranslation and system memory cache services. In addition, theaccelerator integration circuit 606 may provide virtualizationfacilities for the host processor to manage virtualization of thegraphics processing engines, interrupts, and memory management.

Because hardware resources of the graphics processing engines 601-602, Nare mapped explicitly to the real address space seen by the hostprocessor 605, any host processor can address these resources directlyusing an effective address value. One function of the acceleratorintegration circuit 606, in one embodiment, is the physical separationof the graphics processing engines 601-602, N so that they appear to thesystem as independent units.

As mentioned, in the illustrated embodiment, one or more graphicsmemories 603-604, M are coupled to each of the graphics processingengines 601-602, N, respectively. The graphics memories 603-604, M storeinstructions and data being processed by each of the graphics processingengines 601-602, N. The graphics memories 603-604, M may be volatilememories such as DRAMs (including stacked DRAMs), GDDR memory (e.g.,GDDR5, GDDR6), or HBM, and/or may be non-volatile memories such as 3DXPoint or Nano-Ram.

In one embodiment, to reduce data traffic over link 540, biasingtechniques are used to ensure that the data stored in graphics memories603-604, M is data which will be used most frequently by the graphicsprocessing engines 601-602, N and preferably not used by the cores610-613 (at least not frequently). Similarly, the biasing mechanismattempts to keep data needed by the cores (and preferably not thegraphics processing engines 601-602, N) within the caches 630-633, 626of the cores and system memory 611.

FIG. 7 illustrates another embodiment in which the acceleratorintegration circuit 606 is integrated within the processor 605. In thisembodiment, the graphics processing engines 601-602, N communicatedirectly over the high-speed link 540 to the accelerator integrationcircuit 606 via interface 607 and interface 635 (which, again, may beutilize any form of bus or interface protocol). The acceleratorintegration circuit 606 may perform the same operations as thosedescribed with respect to FIG. 6, but potentially at a higher throughputgiven its close proximity to the coherency bus 620 and caches 630-633,626.

One embodiment supports different programming models including adedicated-process programming model (no graphics acceleration modulevirtualization) and shared programming models (with virtualization). Thelatter may include programming models which are controlled by theaccelerator integration circuit 606 and programming models which arecontrolled by the graphics acceleration module 616.

In one embodiment of the dedicated process model, graphics processingengines 601-602, N are dedicated to a single application or processunder a single operating system. The single application can funnel otherapplication requests to the graphics engines 601-602, N, providingvirtualization within a VM/partition.

In the dedicated-process programming models, the graphics processingengines 601-602, N, may be shared by multiple VM/application partitions.The shared models require a system hypervisor to virtualize the graphicsprocessing engines 601-602, N to allow access by each operating system.For single-partition systems without a hypervisor, the graphicsprocessing engines 601-602, N are owned by the operating system. In bothcases, the operating system can virtualize the graphics processingengines 601-602, N to provide access to each process or application.

For the shared programming model, the graphics acceleration module 616or an individual graphics processing engine 601-602, N selects a processelement using a process handle. In one embodiment, process elements arestored in system memory 611 and are addressable using the effectiveaddress to real address translation techniques described herein. Theprocess handle may be an implementation-specific value provided to thehost process when registering its context with the graphics processingengine 601-602, N (that is, calling system software to add the processelement to the process element linked list). The lower 16-bits of theprocess handle may be the offset of the process element within theprocess element linked list.

FIG. 8 illustrates an exemplary accelerator integration slice 830. Asused herein, a “slice” comprises a specified portion of the processingresources of the accelerator integration circuit 606. Applicationeffective address space 821 within system memory 611 stores processelements 826. In one embodiment, the process elements 826 are stored inresponse to GPU invocations 813 from applications 811 executed on theprocessor 605. A process element 826 contains the process state for thecorresponding application 811. A work descriptor (WD) 823 contained inthe process element 826 can be a single job requested by an applicationor may contain a pointer to a queue of jobs. In the latter case, the WD823 is a pointer to the job request queue in the application's addressspace 821.

The graphics acceleration module 616 and/or the individual graphicsprocessing engines 601-602, N can be shared by all or a subset of theprocesses in the system. Embodiments of the invention include aninfrastructure for setting up the process state and sending a WD 823 toa graphics acceleration module 616 to start a job in a virtualizedenvironment.

In one implementation, the dedicated-process programming model isimplementation-specific. In this model, a single process owns thegraphics acceleration module 616 or an individual graphics processingengine 601. Because the graphics acceleration module 616 is owned by asingle process, the hypervisor initializes the accelerator integrationcircuit 606 for the owning partition and the operating systeminitializes the accelerator integration circuit 606 for the owningprocess at the time when the graphics acceleration module 616 isassigned.

In operation, a WD fetch unit 831 in the accelerator integration slice830 fetches the next WD 823 which includes an indication of the work tobe done by one of the graphics processing engines of the graphicsacceleration module 616. Data from the WD 823 may be stored in registers615 and used by the memory management unit (MMU) 609, interruptmanagement circuit 617 and/or context management circuit 616 asillustrated. For example, one embodiment of the MMU 609 includessegment/page walk circuitry for accessing segment/page tables 824 withinthe OS virtual address space 827. The interrupt management circuit 617may process interrupt events 852 received from the graphics accelerationmodule 616. When performing graphics operations, an effective address851 generated by a graphics processing engine 601-602, N is translatedto a real address by the MMU 609.

In one embodiment, the same set of registers 615 are duplicated for eachgraphics processing engine 601-602, N and/or graphics accelerationmodule 616 and may be initialized by the hypervisor or operating system.Each of these duplicated registers may be included in an acceleratorintegration slice 830. Exemplary registers that may be initialized bythe hypervisor are shown in Table 1.

TABLE 1 Hypervisor Initialized Registers 1 Slice Control Register 2 RealAddress (RA) Scheduled Processes Area Pointer 3 Authority Mask OverrideRegister 4 Interrupt Vector Table Entry Offset 5 Interrupt Vector TableEntry Limit 6 State Register 7 Logical Partition ID 8 Real address (RA)Hypervisor Accelerator Utilization Record Pointer 9 Storage DescriptionRegister

Exemplary registers that may be initialized by the operating system areshown in Table 2.

TABLE 2 Operating System Initialized Registers 1 Process and ThreadIdentification 2 Effective Address (EA) Context Save/Restore Pointer 3Virtual Address (VA) Accelerator Utilization Record Pointer 4 VirtualAddress (VA) Storage Segment Table Pointer 5 Authority Mask 6 Workdescriptor

In one embodiment, each WD 823 is specific to a particular graphicsacceleration module 616 and/or graphics processing engine 601-602, N. Itcontains all the information a graphics processing engine 601-602, Nrequires to do its work, or it can be a pointer to a memory locationwhere the application has set up a command queue of work to becompleted.

FIG. 9 illustrates additional details for one embodiment of a sharedmodel. This embodiment includes a hypervisor real address space 911 inwhich a process element list 912 is stored. The hypervisor real addressspace 911 is accessible via a hypervisor 902 which virtualizes thegraphics acceleration module engines for the operating system 901.

The shared programming models allow for all or a subset of processesfrom all or a subset of partitions in the system to use a graphicsacceleration module 616. There are two programming models where thegraphics acceleration module 616 is shared by multiple processes andpartitions: time-sliced shared and graphics directed shared.

In this model, the system hypervisor 902 owns the graphics accelerationmodule 616 and makes its function available to all operating systems901. For a graphics acceleration module 616 to support virtualization bythe system hypervisor 902, the graphics acceleration module 616 mayadhere to the following requirements: 1) An application's job requestmust be autonomous (that is, the state does not need to be maintainedbetween jobs), or the graphics acceleration module 616 must provide acontext save and restore mechanism. 2) An application's job request isguaranteed by the graphics acceleration module 616 to complete in aspecified amount of time, including any translation faults, or thegraphics acceleration module 616 provides the ability to preempt theprocessing of the job. 3) The graphics acceleration module 616 must beguaranteed fairness between processes when operating in the directedshared programming model.

In one embodiment, for the shared model, the application 811 is requiredto make an operating system 901 system call with a graphics accelerationmodule 616 type, a work descriptor (WD), an authority mask register(AMR) value, and a context save/restore area pointer (CSRP). Thegraphics acceleration module 616 type describes the targetedacceleration function for the system call. The graphics accelerationmodule 616 type may be a system-specific value. The WD is formattedspecifically for the graphics acceleration module 616 and can be in theform of a graphics acceleration module 616 command, an effective addresspointer to a user-defined structure, an effective address pointer to aqueue of commands, or any other data structure to describe the work tobe done by the graphics acceleration module 616. In one embodiment, theAMR value is the AMR state to use for the current process. The valuepassed to the operating system is similar to an application setting theAMR. If the accelerator integration circuit 606 and graphicsacceleration module 616 implementations do not support a User AuthorityMask Override Register (UAMOR), the operating system may apply thecurrent UAMOR value to the AMR value before passing the AMR in thehypervisor call. The hypervisor 902 may optionally apply the currentAuthority Mask Override Register (AMOR) value before placing the AMRinto the process element 826. In one embodiment, the CSRP is one of theregisters 610 containing the effective address of an area in theapplication's address space 821 for the graphics acceleration module 616to save and restore the context state. This pointer is optional if nostate is required to be saved between jobs or when a job is preempted.The context save/restore area may be pinned system memory.

Upon receiving the system call, the operating system 901 may verify thatthe application 811 has registered and been given the authority to usethe graphics acceleration module 616. The operating system 901 thencalls the hypervisor 902 with the information shown in Table 3.

TABLE 3 OS to Hypervisor Call Parameters 1 A work descriptor (WD) 2 AnAuthority Mask Register (AMR) value (potentially masked). 3 An effectiveaddress (EA) Context Save/Restore Area Pointer (CSRP) 4 A process ID(PID) and optional thread ID (TID) 5 A virtual address (VA) acceleratorutilization record pointer (AURP) 6 The virtual address of the storagesegment table pointer (SSTP) 7 A logical interrupt service number (LISN)

Upon receiving the hypervisor call, the hypervisor 902 verifies that theoperating system 901 has registered and been given the authority to usethe graphics acceleration module 616. The hypervisor 902 then puts theprocess element 826 into the process element linked list for thecorresponding graphics acceleration module 616 type. The process elementmay include the information shown in Table 4.

TABLE 4 Process Element Information 1 A work descriptor (WD) 2 AnAuthority Mask Register (AMR) value (potentially masked). 3 An effectiveaddress (EA) Context Save/Restore Area Pointer (CSRP) 4 A process ID(PID) and optional thread ID (TID) 5 A virtual address (VA) acceleratorutilization record pointer (AURP) 6 The virtual address of the storagesegment table pointer (SSTP) 7 A logical interrupt service number (LISN)8 Interrupt vector table, derived from the hypervisor call parameters. 9A state register (SR) value 10 A logical partition ID (LPID) 11 A realaddress (RA) hypervisor accelerator utilization record pointer 12 TheStorage Descriptor Register (SDR)

In one embodiment, the hypervisor initializes a plurality of acceleratorintegration slice 830 registers 610.

As illustrated in FIG. 10, one embodiment of the invention employs aunified memory 1000 addressable via a common virtual memory addressspace used to access the physical processor memories 501-502 and GPUmemories 520-523. In this implementation, operations executed on theGPUs 510-513 utilize the same virtual/effective memory address space toaccess the processors memories 501-502 and vice versa, therebysimplifying programmability. In one embodiment, a first portion of thevirtual/effective address space is allocated to the processor memory501, a second portion to the second processor memory 502, a thirdportion to the GPU memory 520, and so on. The entire virtual/effectivememory space (sometimes referred to as the effective address space) isthereby distributed across each of the processor memories 501-502 andGPU memories 520-523, allowing any processor or GPU to access anyphysical memory with a virtual address mapped to that memory.

In one embodiment, bias/coherence management circuitry 920-924 withinone or more of the MMUs 1010-1014 ensures cache coherence between thecaches of the host processors (e.g., 505) and the GPUs 510-513 and alsoimplements biasing techniques indicating the physical memories in whichcertain types of data should be stored. While multiple instances ofbias/coherence management circuitry 920-924 are illustrated in FIG. 10,the bias/coherence circuitry may be implemented within the MMU of one ormore host processors 1005 and/or within the accelerator integrationcircuit 606.

One embodiment allows GPU-attached memory 520-523 to be mapped as partof system memory and accessed using shared virtual memory (SVM)technology, but without suffering the typical performance drawbacksassociated with full system cache coherence. The ability to GPU-attachedmemory 520-523 to be accessed as system memory without onerous cachecoherence overhead provides a beneficial operating environment for GPUoffload. This arrangement allows the host processor 505 software tosetup operands and access computation results, without the overhead oftradition I/O DMA data copies. Such traditional copies involve drivercalls, interrupts and memory mapped I/O (MMIO) accesses that are allinefficient relative to simple memory accesses. At the same time, theability to access GPU attached memory 520-523 without cache coherenceoverheads can be critical to the execution time of an offloadedcomputation. In cases with substantial streaming write memory traffic,for example, cache coherence overhead can significantly reduce theeffective write bandwidth seen by a GPU 510-513. The efficiency ofoperand setup, the efficiency of results access, and the efficiency ofGPU computation all play a role in determining the effectiveness of GPUoffload.

In one implementation, the selection of between GPU bias and hostprocessor bias is driven by a bias tracker data structure. A bias tablemay be used, for example, which may be a page-granular structure (i.e.,controlled at the granularity of a memory page) that includes 1 or 2bits per GPU-attached memory page. The bias table may be implemented ina stolen memory range of one or more GPU-attached memories 520-523, withor without a bias cache in the GPU 510-513 (e.g., to cachefrequently/recently used entries of the bias table). Alternatively, theentire bias table may be maintained within the GPU 510 itself.

In one implementation, the bias table entry associated with each accessto the GPU-attached memory 520-523 is accessed prior the actual accessto the GPU memory, causing the following operations. First, localrequests from the GPU 510 that find their page in GPU bias are forwardeddirectly to GPU memory 520. Local requests from the GPU 510 that findtheir page in host bias are forwarded to the processor 505 (e.g., over ahigh speed link as discussed above). In one embodiment, requests fromthe processor 505 that find the requested page in host processor biascomplete the request like a normal memory read. Alternatively, requestsdirected to a GPU-biased page may be forwarded to the GPU 510. The GPUmay then transition the page to a host processor bias if it is notcurrently using the page.

The bias state of a page can be changed either by a software-basedmechanism, a hardware-assisted software-based mechanism, or, for alimited set of cases, a purely hardware-based mechanism.

One mechanism for changing the bias state employs an API call (e.g.OpenCL), which, in turn, calls the GPU's device driver which, in turn,sends a message (or enqueues a command descriptor) to the GPU directingit to change the bias state and, for some transitions, perform a cacheflushing operation in the host. The cache flushing operation is requiredfor a transition from host processor 505 bias to GPU bias, but is notrequired for the opposite transition.

In one embodiment, cache coherency is maintained by temporarilyrendering GPU-biased pages uncacheable by the host processor 505. Inorder to access these pages, the processor 505 may request access fromthe GPU 510 which may or may not grant access right away, depending onthe implementation. Thus, to reduce communication between the processor505 and GPU 510 it is beneficial to ensure that GPU-biased pages arethose which are required by the GPU but not the host processor 505 andvice versa.

Graphics Processing Pipeline

FIG. 11 is a conceptual diagram of a graphics processing pipeline 1100,according to an embodiment. In one embodiment a graphics processor canimplement the illustrated graphics processing pipeline 1100. Thegraphics processor can be included within the parallel processingsubsystems as described herein, such as the parallel processor 200 ofFIG. 2, which, in one embodiment, is a variant of the parallelprocessor(s) 112 of FIG. 1. The various parallel processing systems canimplement the graphics processing pipeline 1100 via one or moreinstances of the parallel processing unit (e.g., parallel processingunit 202 of FIG. 2) as described herein. For example, a shader unit(e.g., graphics multiprocessor 304 of FIG. 3) may be configured toperform the functions of one or more of a vertex processing unit 1104, atessellation control processing unit 1108, a tessellation evaluationprocessing unit 1112, a geometry processing unit 1116, and afragment/pixel processing unit 1124. The functions of data assembler1102, primitive assemblers 1106, 1114, 1118, tessellation unit 1110,rasterizer 1122, and raster operations unit 1126 may also be performedby other processing engines within a processing cluster (e.g.,processing cluster 314 of FIG. 3) and a corresponding partition unit(e.g., partition unit 220A-220N of FIG. 2). Alternately, the graphicsprocessing pipeline 1100 may be implemented using dedicated processingunits for one or more functions. In one embodiment, one or more portionsof the graphics processing pipeline 1100 can be performed in by aparallel processing logic within a general purpose processor (e.g.,CPU). In one embodiment, one or more portions of the graphics processingpipeline 1100 can access on-chip memory (e.g., parallel processor memory222 as in FIG. 2) via a memory interface 1128, which may be an instanceof the memory interface 218 of FIG. 2.

In one embodiment the data assembler 1102 is a processing unit thatcollects vertex data for high-order surfaces, primitives, etc., andoutputs the vertex data, including the vertex attributes, to the vertexprocessing unit 1104. The vertex processing unit 1104 is a programmableexecution unit that is configured to execute vertex shader programs,lighting and transforming vertex data as specified by the vertex shaderprograms. For example, vertex processing unit 1104 may be programmed totransform the vertex data from an object-based coordinate representation(object space) to an alternatively based coordinate system such as worldspace or normalized device coordinates (NDC) space. Vertex processingunit 1104 may read data that is stored in cache, local or system memoryfor use in processing the vertex data.

A first instance of a primitive assembler 1106 receives vertexattributes from the vertex processing unit 1104, reading stored vertexattributes as needed, and constructs graphics primitives for processingby tessellation control processing unit 1108, where the graphicsprimitives include triangles, line segments, points, patches, and soforth, as supported by various graphics processing applicationprogramming interfaces (APIs).

The tessellation control processing unit 1108 treats the input verticesas control points for a geometric patch and transforms these controlpoints from the patch's input representation, often called the patch'sbasis, into a representation suitable for efficient surface evaluationby the tessellation evaluation processing unit 1112. The tessellationcontrol processing unit 1108 also computes tessellation factors foredges of geometric patches. A tessellation factor applies to a singleedge and quantifies a view-dependent level of detail associated with theedge. A tessellation unit 1110 is configured to receive the tessellationfactors for edges of a patch and to tessellate the patch into multiplegeometric primitives such as line, triangle, or quadrilateralprimitives, which are transmitted to a tessellation evaluationprocessing unit 1112. The tessellation evaluation processing unit 1112operates on parameterized coordinates of the subdivided patch togenerate a surface representation and vertex attributes for each vertexassociated with the geometric primitives.

A second instance of a primitive assembler 1114 receives vertexattributes from the tessellation evaluation processing unit 1112,reading stored vertex attributes as needed, and constructs graphicsprimitives for processing by the geometry processing unit 1116. Thegeometry processing unit 1116 is a programmable execution unit that isconfigured to execute geometry shader programs, transforming graphicsprimitives received from primitive assembler 1114 as specified by thegeometry shader programs. For example, the geometry processing unit 1116may be programmed to subdivide the graphics primitives into one or morenew graphics primitives and calculate parameters, such as plane equationcoefficients, that are used to rasterize the new graphics primitives.

In some embodiments the geometry processing unit 1116 may also add ordelete elements in the geometry stream. Geometry processing unit 1116outputs the parameters and vertices specifying new graphics primitivesto primitive assembler 1118, which receives the parameters and verticesfrom the geometry processing unit 1116, reading stored vertexattributes, as needed, and constructs graphics primitives for processingby a viewport scale, cull, and clip unit 1120. The geometry processingunit 1116 may read data that is stored in parallel processor memory orsystem memory for use in processing the geometry data. The viewportscale, cull, and clip unit 1120 performs clipping, culling, and viewportscaling and outputs processed graphics primitives to a rasterizer 1122.

The rasterizer 1122 scan converts the new graphics primitives andoutputs fragment and coverage data to the fragment/pixel processing unit1124. Additionally, the rasterizer 1122 may be configured to perform zculling and other z-based optimizations.

The fragment/pixel processing unit 1124 is a programmable execution unitthat is configured to execute fragment shader programs or pixel shaderprograms. The fragment/pixel processing unit 1124 transforming fragmentsor pixels received from rasterizer 1122, as specified by the fragment orpixel shader programs. For example, the fragment/pixel processing unit1124 may be programmed to perform operations such as perspectivecorrection, texture mapping, shading, blending, and the like, to produceshaded fragments or pixels that are output to raster operations unit1126. The fragment/pixel processing unit 1124 may read data that isstored in parallel processor memory or system memory for use inprocessing the fragment data. Fragment or pixel shader programs may beconfigured to shade at the sample, pixel, tile, or other granularity,depending on the programmed sampling rate.

The raster operations unit 1126 is a processing unit that performsraster operations, such as stencil, z test, blending, and the like, andoutputs pixel data as processed graphics data for storage in graphicsmemory. The processed graphics data may be stored in graphics memory,e.g., parallel processor memory 222 as in FIG. 2, and/or system memory104 as in FIG. 1, for display on one of the one or more displaydevice(s) 110 or for further processing by one of the one or moreprocessor(s) 102 or parallel processor(s) 112. In some embodiments theraster operations unit 1126 is configured to compress z or color datathat is written to memory and decompress z or color data that is readfrom memory.

FIG. 12 illustrates a subsystem 1200 for spawning threads within asingle-instruction multiple-data (SIMD) computation system, according toan embodiment. The subsystem 1200 includes a front end 1208, ascheduler, and a processing cluster 1214, which, in one embodiment, arerespective instances of the front end 208, scheduler 210, and any ofcluster 214A-214N of the processing cluster array 212 shown in FIG. 2.In such embodiment, the front end is in communication with a hostinterface, such as the host interface 206 of FIG. 2. In one embodimentthe processing cluster 1214 is a variant of the processing cluster 300of FIG. 3. The processing cluster 1214 includes a pipeline manager 1202and graphics multiprocessors 1204A-1204N. Each of the graphicsmultiprocessors 1204A-1204N can be similar to the graphicsmultiprocessor 304 of the processing cluster 300 of FIG. 3, although inone embodiment one of more instances of the graphics multiprocessors1204A-1204N can differ slightly in capabilities. The pipeline manager1202 can be a variant of the pipeline manager 302 of FIG. 3A and isconfigured to manager execution of thread groups on the graphicsmultiprocessors 1204A-1204N.

The processing cluster 1214 can execute graphics and general-purposecomputations using thread groups. A thread group consists of a number ofthreads that concurrently execute the same program on an input data setto produce an output data set. The size of a thread group can vary andembodiments are not limited to any particular thread group size,although thread groups are generally scheduled with a number of threadsthat is a power of two (e.g., 16, 32, 64, 128, etc.). Each thread in thethread group is assigned a unique thread identifier (e.g., thread ID)that is accessible to the thread during its execution. The thread IDcontrols various aspects of the thread's processing behavior, such asdetermining which portion of the input data set a thread is to processand/or determining which portion of an output data set a thread is toproduce or write.

When processing a graphics or computational workload, the scheduler 1210receives a request from the front end 1208 to schedule thread groups onthe graphics multiprocessors 1204A-1204N of the processing cluster 1214.The request can include a reference to a thread program to execute. Thecollection of threads of the thread program can be executed as a threadgrid including one or more thread groups configured to execute on theprocessing cluster 1214. Each thread group includes one or moreindividual threads. In one embodiment, when a scheduler 1210 schedules athread group to the processing cluster 1214, the pipeline manager 1202assigns the thread group to one of the graphics multiprocessors1204A-1204C.

In previous implementations, thread groups are scheduled to the graphicsmultiprocessors 1204A-1204N at thread group granularity. In other words,a thread group is scheduled to a graphics multiprocessor and executes onthe graphics multiprocessor until all threads in the thread group arecomplete. In embodiments described herein, pipeline submissions areperformed across the set of graphics multiprocessors 1204A-1204N withina processing cluster 1214 at sub-group granularity, such that uponcompletion of a thread sub-group on a graphics multiprocessor, asub-group from a different thread group can be scheduled to the graphicsmultiprocessor. In some embodiments the number of threads within eachsub-group of a thread group is programmable. In one embodiment thenumber of sub-groups can contain any even number division of threadswithin a thread group. For example, if an exemplary thread groupcontains 64 threads, a number of sub-thread groups can be configuredcontaining any of 2, 4, 8, 16, or 32 threads. In other words, theexemplary thread group can be divided into any of 32, 16, 8, 4, or 2sub-groups, although these numbers are exemplary and not limiting as toany one embodiment.

FIG. 13 illustrates a subsystem 1300 for managing thread groups andsub-groups on an execution pipeline of a general purpose graphicsprocessing unit, according to an embodiment. In one embodiment thesubsystem 1300 includes a pipeline manager 1302, which may be a variantof the pipeline manager 302 of FIG. 3A and/or the pipeline manager 1202of FIG. 12. The pipeline manager 1302 includes a thread group manager1310 to manage scheduling of thread groups and sub-groups to theexecution pipeline of the graphics processor. The execution pipeline caninclude variants of the graphics multiprocessors 1204A-1204N of FIG. 12.In some embodiments the execution pipeline can also include additionalexecution resources other than the graphics multiprocessors, includingspecial function units. In one embodiment the thread group manager 1310includes a thread group counter 1312, a group ID FIFO 1313 (first-in,first-out buffer), a group ID FIFO manager 1314, a sub-group ID FIFO1316, a sub-group ID FIFO manager 1317, sub-group thread counters 1318,a launch unit 1319, and a run queue 1320. While some embodimentsdescribed herein illustrate logic within the thread group manager 1310to handle thread submission or execution at sub-group granularity, otherembodiments can include sub-group logic within other schedulingcomponents, such as the scheduler 1210 as in FIG. 12. In suchembodiments, similar logic as illustrated within the thread groupmanager 1310 is included within a scheduler 1210 of FIG. 12, or otherscheduling logic external to the processing cluster 1214 of FIG. 12.

In one embodiment the thread group counter 1312 includes a count of thenumber of thread groups that have active sub-groups within the executionpipeline. The thread group counter 1312 includes one or more counterregisters to store a count value and logic to increment or decrement thecount values stored in the one or more counter registers. The group IDFIFO 1313 is a first-in, first-out buffer that stores group identifiersfor thread groups that are active in the execution pipeline. A group IDFIFO manager 1314 includes logic to allocate group identifiers forthread groups and insert the group identifiers into the group ID FIFO1313. The sub-group ID FIFO 1316 is a first-in, first-out buffer thatstores group identifiers for thread sub-groups that are active in theexecution pipeline. The sub-group ID FIFO manager 1317 includes logic toallocate sub-group identifiers for thread sub-groups and insert thesub-group identifiers into the sub-group ID FIFO 1316.

In one embodiment the sub-group ID FIFO manager 1317 allocates eachsub-group identifier based on the thread group associated withsub-group, such that the pipeline manager 1302 and logic within theexecution pipeline can determine the thread group identifier that isassociated with any given thread sub-group. In one embodiment, metadatais associated with each individual thread that contains the thread groupidentifier and the thread sub-group identifier to which the thread isassigned. In one embodiment the thread group identifier and sub-groupidentifier are accessible to the thread during execution.

The sub-group thread counters 1318 are multiple sets of counters, witheach counter associated with separate sub-group. The sub-group threadcounters 1318 include registers to store an active thread count valuefor each thread sub-group and logic to increment or decrement the activethread count value for each sub-group. The launch unit 1319 includeslogic to dispatch the threads in a thread sub-group to the executionpipeline. Identifiers for executing threads can be stored in the runqueue 1320 while the threads are being executed by the executionpipeline. In one embodiment, individual thread identifiers are stored inthe run queue 1320. In one embodiment, sub-group identifiers can bestored in the run queue in addition to or in place of individual threadidentifiers.

When a thread group is to be launched the thread group identifier ispushed onto the group ID FIFO 1313 by the Group ID FIFO manager 1314.The identifier of each sub-group associated with the thread groupidentifier is also pushed onto the sub-group ID FIFO 1316 by thesub-group ID FIFO manager 1317. The launch unit 1319 can then launcheach thread of the thread group and associated thread sub-groups.

In one embodiment the launch unit 1319 is configured to launch eachthread of a thread group when the identifier of the thread group ispushed onto the group ID FIFO 1313. In such embodiment the launch unit1319 will attempt to launch the sub-groups of the thread group based onavailable execution resources within the execution pipeline. Forexample, when the execution pipeline is starting from an idle state, allsub-groups of a thread group can be launched by the launch unit 1319 andthe thread group counter 1312 can be incremented to indicate that athread group is executing on the execution pipeline. The sub-group IDFIFO manager 1317 can then push the identifier of each sub-group intothe sub-group ID FIFO 1316. The counters for the respective sub-groupsare incremented in the sub-group thread counters 1318 for each thread inthe respective sub-groups.

As threads within the sub-groups complete execution within the executionpipeline, the sub-group thread counters 1318 are decremented. When allthreads in a thread sub-group complete execution the counter of thethread sub-group will be decremented to zero and the thread sub-groupcan be retired. Thread sub-groups may be independently retired, suchthat thread sub-groups may retire when complete without requiring allsub-groups of a thread group to be complete. In one embodiment thelaunch unit 1319 is configured to remove identifiers for retired threadsand/or sub-groups from the run queue 1320 when the thread sub-group iscomplete. While the run queue 1320 is illustrated as separate from thethread group manager 1310, in one embodiment the run queue 1320 can be acomponent of the launch unit 1319 within the thread group manager 1310.

As thread sub-groups are retired and execution resources within theexecution pipeline become available, the launch unit 1319 can launchthreads associated with sub-groups of a pending thread group. Threadscan continue to be assigned at sub-group granularity until all pendingthread groups and associated sub-groups complete execution. Once allsub-groups of a thread group complete execution, the thread groupcounter 1312 is decremented.

When dispatching threads at a sub-group granularity, a graphicsmultiprocessor within the execution pipeline may execute threads fromdifferent thread groups. As sub-groups of a first thread group completeexecution, thread sub-groups from a different thread group can belaunched on the graphics multiprocessor before all sub-groups of thethread group are complete.

FIG. 14 illustrates execution of thread sub-groups within a graphicsmultiprocessor, according to an embodiment. In one embodiment a runqueue 1402 includes identifiers for threads that have been dispatched toa graphics multiprocessor 1410. The graphics multiprocessor 1410 can beany graphics multiprocessor 1410 described herein, including graphicsmultiprocessor 304 of FIG. 3A, graphics multiprocessor 400 of FIG. 4A,and/or any of graphics multiprocessor 1204A-1204N of FIG. 12. The runqueue 1402, in one embodiment, is a variant of the run queue 1320 ofFIG. 13 and contains identifiers associated with threads that have beendispatched for execution on a graphics multiprocessor 1410. A sub-groupretirement queue 1420 is illustrated that contains identifiers forthreads and/or thread sub-groups that have completed execution and arein the process of being retired.

In the illustrated run queue 1402, multiple thread groups, for example,thread group 1404, thread group 1406, and thread group 1408, have beendispatched for execution on the graphics multiprocessor 1410. While thenumber of thread groups can vary across and within embodiments, eachthread group is shown with four exemplary sub-groups. In one embodiment,if the graphics multiprocessor 1410 is starting at an idle state, allthread sub-groups of one or more thread groups can be executed. Forexample, all sub-groups of thread group 1404 and thread group 1406 canbe executed on the graphics multiprocessor 1410 while thread group 1408waits for execution in the run queue 1402. When initially launched, allsub-groups of a thread group can be launched on the graphicsmultiprocessor 1410. Sub-groups of a thread group will not necessarilycomplete at the same rate, so some thread sub-groups may complete beforeother thread sub-groups. For example, if thread sub-group 1404C andthread sub-group 1404D complete before thread sub-groups 1404A andthread sub-group 1404B, thread sub-groups 1404C, 1404D are removed fromthe graphics multiprocessor 1410 and identifiers associated with thecompleted thread sub-groups can be placed into a sub-group retirementqueue 1420. Similar operations can occur should thread sub-group 1406Aand thread sub-group 1406B complete before thread sub-group 1406C andthread sub-group 1406D. In one embodiment, retired thread sub-groups aretracked via the sub-group retirement queue 1420 until all sub-groups ofa thread group are complete.

In embodiments described herein, the vacant execution resources withinthe graphics multiprocessor 1410 left by the completed thread sub-groups1404C, 1404D, 1406A, 1406B can be filled with threads of a pendingthread group. For example, thread sub-group 1408A, thread sub-group1408B, thread sub-group 1408C, and thread sub-group 1408D of threadgroup 1408 can be executed on the graphics multiprocessor 1410 beforeall threads of thread group 1404 and thread group 1406 are complete.

In one embodiment a thread within one thread sub-group can havedependencies upon a thread within a different sub-group. In suchembodiment, a scoreboard can be maintained to track dependencies betweenthe different thread sub-groups. If a first thread sub-group isdependent on a status of execution of a second thread sub-group, thescoreboard can prevent execution of instructions within a thread untilthe dependencies are satisfied. For example and in one embodiment, if athread in thread sub-group 1408A is dependent upon the outcome of athread in thread sub-group 1408B, thread sub-groups 1408B-1408C canexecute on the graphics multiprocessor while some other thread sub-groupis executed. Thread sub-group 1408A can then execute once threadsub-group 1408B completes. Alternatively, one embodiment can beconfigured to launch thread sub-group 1408A along with thread sub-group1408B. For example, if no additional thread sub-groups are pending, itmay be beneficial to launch the threads of thread sub-group 1408A andprevent issue or execution of thread instructions (e.g., via barrierinstructions, scoreboard logic, etc.) until the dependent data fromthread sub-group 1408B is available.

FIG. 15 is a flow diagram of logic 1500 to launch thread sub-groups on agraphics multiprocessor, according to an embodiment. The logic 1500 canbe included within hardware or firmware logic of a scheduler or pipelinemanager as described herein. The logic 1500 is configured to launchthreads on a graphics multiprocessor at sub-group granularity whilerespecting dependencies between threads in differing sub-groups.

In one embodiment the logic is configured to launch thread sub-groupsfor a thread group on a multiprocessor unit, as shown at 1502. Whenstarting from an idle state, all sub-groups of a thread group can belaunched on the graphics multiprocessor. Once a thread sub-group of athread group completes, as determined at 1503, the logic 1500 canretired the completed sub-group at 1504. In one embodiment, retiring acompleted sub-group includes storing an identifier for the completedsub-group in a retired thread sub-group until all sub-groups of a threadgroup are complete.

The logic 1500 can fill any idle execution resources within a graphicsmultiprocessor having completed thread sub-groups by launchingadditional thread sub-groups. The additional thread sub-groups can beassociated with a different thread group than any currently executingthread groups. In one embodiment, threads within a thread group can havecross sub-group dependencies. Additionally, threads within a sub-groupcan have dependencies on shared resources within the graphicsmultiprocessor. Accordingly, dependencies for each thread sub-group canbe tracked. Before launching additional thread sub-groups the logic 1500can check the dependencies of pending thread sub-groups, as shown at1506. If the logic 1500 determines at 1507 that a pending threadsub-group is ready to launch (e.g., has no unsatisfied dependencies),the logic 1500 can launch one or more pending sub-groups on themultiprocessor unit, as shown at 1508. During normal operation the logic1500 can continue to perform the illustrated operations until the threadsub-groups of the pending thread groups have completed execution.

Additional Exemplary Graphics Processing System

Details of the embodiments described above can be incorporated withingraphics processing systems and devices described below. The graphicsprocessing system and devices of FIG. 16 through FIG. 29 illustratealternative systems and graphics processing hardware that can implementany and all of the techniques described above.

Additional Exemplary Graphics Processing System Overview

FIG. 16 is a block diagram of a processing system 1600, according to anembodiment. In various embodiments the system 1600 includes one or moreprocessors 1602 and one or more graphics processors 1608, and may be asingle processor desktop system, a multiprocessor workstation system, ora server system having a large number of processors 1602 or processorcores 1607. In one embodiment, the system 1600 is a processing platformincorporated within a system-on-a-chip (SoC) integrated circuit for usein mobile, handheld, or embedded devices.

An embodiment of system 1600 can include, or be incorporated within aserver-based gaming platform, a game console, including a game and mediaconsole, a mobile gaming console, a handheld game console, or an onlinegame console. In some embodiments system 1600 is a mobile phone, smartphone, tablet computing device or mobile Internet device. Dataprocessing system 1600 can also include, couple with, or be integratedwithin a wearable device, such as a smart watch wearable device, smarteyewear device, augmented reality device, or virtual reality device. Insome embodiments, data processing system 1600 is a television or set topbox device having one or more processors 1602 and a graphical interfacegenerated by one or more graphics processors 1608.

In some embodiments, the one or more processors 1602 each include one ormore processor cores 1607 to process instructions which, when executed,perform operations for system and user software. In some embodiments,each of the one or more processor cores 1607 is configured to process aspecific instruction set 1609. In some embodiments, instruction set 1609may facilitate Complex Instruction Set Computing (CISC), ReducedInstruction Set Computing (RISC), or computing via a Very LongInstruction Word (VLIW). Multiple processor cores 1607 may each processa different instruction set 1609, which may include instructions tofacilitate the emulation of other instruction sets. Processor core 1607may also include other processing devices, such a Digital SignalProcessor (DSP).

In some embodiments, the processor 1602 includes cache memory 1604.Depending on the architecture, the processor 1602 can have a singleinternal cache or multiple levels of internal cache. In someembodiments, the cache memory is shared among various components of theprocessor 1602. In some embodiments, the processor 1602 also uses anexternal cache (e.g., a Level-3 (L3) cache or Last Level Cache (LLC))(not shown), which may be shared among processor cores 1607 using knowncache coherency techniques. A register file 1606 is additionallyincluded in processor 1602 which may include different types ofregisters for storing different types of data (e.g., integer registers,floating point registers, status registers, and an instruction pointerregister). Some registers may be general-purpose registers, while otherregisters may be specific to the design of the processor 1602.

In some embodiments, processor 1602 is coupled with a processor bus 1610to transmit communication signals such as address, data, or controlsignals between processor 1602 and other components in system 1600. Inone embodiment the system 1600 uses an exemplary ‘hub’ systemarchitecture, including a memory controller hub 1616 and an Input Output(I/O) controller hub 1630. A memory controller hub 1616 facilitatescommunication between a memory device and other components of system1600, while an I/O Controller Hub (ICH) 1630 provides connections to I/Odevices via a local I/O bus. In one embodiment, the logic of the memorycontroller hub 1616 is integrated within the processor.

Memory device 1620 can be a dynamic random-access memory (DRAM) device,a static random access memory (SRAM) device, flash memory device,phase-change memory device, or some other memory device having suitableperformance to serve as process memory. In one embodiment the memorydevice 1620 can operate as system memory for the system 1600, to storedata 1622 and instructions 1621 for use when the one or more processors1602 executes an application or process. Memory controller hub 1616 alsocouples with an optional external graphics processor 1612, which maycommunicate with the one or more graphics processors 1608 in processors1602 to perform graphics and media operations.

In some embodiments, ICH 1630 enables peripherals to connect to memorydevice 1620 and processor 1602 via a high-speed I/O bus. The I/Operipherals include, but are not limited to, an audio controller 1646, afirmware interface 1628, a wireless transceiver 1626 (e.g., Wi-Fi,Bluetooth), a data storage device 1624 (e.g., hard disk drive, flashmemory, etc.), and a legacy I/O controller 1640 for coupling legacy(e.g., Personal System 2 (PS/2)) devices to the system. One or moreUniversal Serial Bus (USB) controllers 1642 connect input devices, suchas keyboard and mouse 1644 combinations. A network controller 1634 mayalso couple with ICH 1630. In some embodiments, a high-performancenetwork controller (not shown) couples with processor bus 1610. It willbe appreciated that the system 1600 shown is exemplary and not limiting,as other types of data processing systems that are differentlyconfigured may also be used. For example, the I/O controller hub 1630may be integrated within the one or more processor 1602, or the memorycontroller hub 1616 and I/O controller hub 1630 may be integrated into adiscreet external graphics processor, such as the external graphicsprocessor 1612.

FIG. 17 is a block diagram of an embodiment of a processor 1700 havingone or more processor cores 1702A-1702N, an integrated memory controller1714, and an integrated graphics processor 1708. Those elements of FIG.17 having the same reference numbers (or names) as the elements of anyother figure herein can operate or function in any manner similar tothat described elsewhere herein but are not limited to such. Processor1700 can include additional cores up to and including additional core1702N represented by the dashed lined boxes. Each of processor cores1702A-1702N includes one or more internal cache units 1704A-1704N. Insome embodiments each processor core also has access to one or moreshared cached units 1706.

The internal cache units 1704A-1704N and shared cache units 1706represent a cache memory hierarchy within the processor 1700. The cachememory hierarchy may include at least one level of instruction and datacache within each processor core and one or more levels of sharedmid-level cache, such as a Level 2 (L2), Level 3 (L3), Level 4 (L4), orother levels of cache, where the highest level of cache before externalmemory is classified as the LLC. In some embodiments, cache coherencylogic maintains coherency between the various cache units 1706 and1704A-1704N.

In some embodiments, processor 1700 may also include a set of one ormore bus controller units 1716 and a system agent core 1710. The one ormore bus controller units 1716 manage a set of peripheral buses, such asone or more Peripheral Component Interconnect buses (e.g., PCI, PCIExpress). System agent core 1710 provides management functionality forthe various processor components. In some embodiments, system agent core1710 includes one or more integrated memory controllers 1714 to manageaccess to various external memory devices (not shown).

In some embodiments, one or more of the processor cores 1702A-1702Ninclude support for simultaneous multi-threading. In such embodiment,the system agent core 1710 includes components for coordinating andoperating cores 1702A-1702N during multi-threaded processing. Systemagent core 1710 may additionally include a power control unit (PCU),which includes logic and components to regulate the power state ofprocessor cores 1702A-1702N and graphics processor 1708.

In some embodiments, processor 1700 additionally includes graphicsprocessor 1708 to execute graphics processing operations. In someembodiments, the graphics processor 1708 couples with the set of sharedcache units 1706, and the system agent core 1710, including the one ormore integrated memory controllers 1714. In some embodiments, a displaycontroller 1711 is coupled with the graphics processor 1708 to drivegraphics processor output to one or more coupled displays. In someembodiments, display controller 1711 may be a separate module coupledwith the graphics processor via at least one interconnect, or may beintegrated within the graphics processor 1708 or system agent core 1710.

In some embodiments, a ring-based interconnect unit 1712 is used tocouple the internal components of the processor 1700. However, analternative interconnect unit may be used, such as a point-to-pointinterconnect, a switched interconnect, or other techniques, includingtechniques well known in the art. In some embodiments, graphicsprocessor 1708 couples with the ring interconnect 1712 via an I/O link1713.

The exemplary I/O link 1713 represents at least one of multiplevarieties of I/O interconnects, including an on package I/O interconnectwhich facilitates communication between various processor components anda high-performance embedded memory module 1718, such as an eDRAM module.In some embodiments, each of the processor cores 1702A-1702N andgraphics processor 1708 use embedded memory modules 1718 as a sharedLast Level Cache.

In some embodiments, processor cores 1702A-1702N are homogenous coresexecuting the same instruction set architecture. In another embodiment,processor cores 1702A-1702N are heterogeneous in terms of instructionset architecture (ISA), where one or more of processor cores 1702A-1702Nexecute a first instruction set, while at least one of the other coresexecutes a subset of the first instruction set or a differentinstruction set. In one embodiment processor cores 1702A-1702N areheterogeneous in terms of microarchitecture, where one or more coreshaving a relatively higher power consumption couple with one or morepower cores having a lower power consumption. Additionally, processor1700 can be implemented on one or more chips or as an SoC integratedcircuit having the illustrated components, in addition to othercomponents.

FIG. 18 is a block diagram of a graphics processor 1800, which may be adiscrete graphics processing unit, or may be a graphics processorintegrated with a plurality of processing cores. In some embodiments,the graphics processor communicates via a memory mapped I/O interface toregisters on the graphics processor and with commands placed into theprocessor memory. In some embodiments, graphics processor 1800 includesa memory interface 1814 to access memory. Memory interface 1814 can bean interface to local memory, one or more internal caches, one or moreshared external caches, and/or to system memory.

In some embodiments, graphics processor 1800 also includes a displaycontroller 1802 to drive display output data to a display device 1820.Display controller 1802 includes hardware for one or more overlay planesfor the display and composition of multiple layers of video or userinterface elements. In some embodiments, graphics processor 1800includes a video codec engine 1806 to encode, decode, or transcode mediato, from, or between one or more media encoding formats, including, butnot limited to Moving Picture Experts Group (MPEG) formats such asMPEG-2, Advanced Video Coding (AVC) formats such as H.264/MPEG-4 AVC, aswell as the Society of Motion Picture & Television Engineers (SMPTE)421M/VC-1, and Joint Photographic Experts Group (JPEG) formats such asJPEG, and Motion JPEG (MJPEG) formats.

In some embodiments, graphics processor 1800 includes a block imagetransfer (BLIT) engine 1804 to perform two-dimensional (2D) rasterizeroperations including, for example, bit-boundary block transfers.However, in one embodiment, 2D graphics operations are performed usingone or more components of graphics processing engine (GPE) 1810. In someembodiments, GPE 1810 is a compute engine for performing graphicsoperations, including three-dimensional (3D) graphics operations andmedia operations.

In some embodiments, GPE 1810 includes a 3D pipeline 1812 for performing3D operations, such as rendering three-dimensional images and scenesusing processing functions that act upon 3D primitive shapes (e.g.,rectangle, triangle, etc.). The 3D pipeline 1812 includes programmableand fixed function elements that perform various tasks within theelement and/or spawn execution threads to a 3D/Media sub-system 1815.While 3D pipeline 1812 can be used to perform media operations, anembodiment of GPE 1810 also includes a media pipeline 1816 that isspecifically used to perform media operations, such as videopost-processing and image enhancement.

In some embodiments, media pipeline 1816 includes fixed function orprogrammable logic units to perform one or more specialized mediaoperations, such as video decode acceleration, video de-interlacing, andvideo encode acceleration in place of, or on behalf of video codecengine 1806. In some embodiments, media pipeline 1816 additionallyincludes a thread spawning unit to spawn threads for execution on3D/Media sub-system 1815. The spawned threads perform computations forthe media operations on one or more graphics execution units included in3D/Media sub-system 1815.

In some embodiments, 3D/Media subsystem 1815 includes logic forexecuting threads spawned by 3D pipeline 1812 and media pipeline 1816.In one embodiment, the pipelines send thread execution requests to3D/Media subsystem 1815, which includes thread dispatch logic forarbitrating and dispatching the various requests to available threadexecution resources. The execution resources include an array ofgraphics execution units to process the 3D and media threads. In someembodiments, 3D/Media subsystem 1815 includes one or more internalcaches for thread instructions and data. In some embodiments, thesubsystem also includes shared memory, including registers andaddressable memory, to share data between threads and to store outputdata.

Additional Exemplary Graphics Processing Engine

FIG. 19 is a block diagram of a graphics processing engine 1910 of agraphics processor in accordance with some embodiments. In oneembodiment, the graphics processing engine (GPE) 1910 is a version ofthe GPE 1810 shown in FIG. 18. Elements of FIG. 19 having the samereference numbers (or names) as the elements of any other figure hereincan operate or function in any manner similar to that describedelsewhere herein, but are not limited to such. For example, the 3Dpipeline 1812 and media pipeline 1816 of FIG. 18 are illustrated. Themedia pipeline 1816 is optional in some embodiments of the GPE 1910 andmay not be explicitly included within the GPE 1910. For example and inat least one embodiment, a separate media and/or image processor iscoupled to the GPE 1910.

In some embodiments, GPE 1910 couples with or includes a commandstreamer 1903, which provides a command stream to the 3D pipeline 1812and/or media pipelines 1816. In some embodiments, command streamer 1903is coupled with memory, which can be system memory, or one or more ofinternal cache memory and shared cache memory. In some embodiments,command streamer 1903 receives commands from the memory and sends thecommands to 3D pipeline 1812 and/or media pipeline 1816. The commandsare directives fetched from a ring buffer, which stores commands for the3D pipeline 1812 and media pipeline 1816. In one embodiment, the ringbuffer can additionally include batch command buffers storing batches ofmultiple commands. The commands for the 3D pipeline 1812 can alsoinclude references to data stored in memory, such as but not limited tovertex and geometry data for the 3D pipeline 1812 and/or image data andmemory objects for the media pipeline 1816. The 3D pipeline 1812 andmedia pipeline 1816 process the commands and data by performingoperations via logic within the respective pipelines or by dispatchingone or more execution threads to a graphics core array 1914.

In various embodiments the 3D pipeline 1812 can execute one or moreshader programs, such as vertex shaders, geometry shaders, pixelshaders, fragment shaders, compute shaders, or other shader programs, byprocessing the instructions and dispatching execution threads to thegraphics core array 1914. The graphics core array 1914 provides aunified block of execution resources. Multi-purpose execution logic(e.g., execution units) within the graphic core array 1914 includessupport for various 3D API shader languages and can execute multiplesimultaneous execution threads associated with multiple shaders.

In some embodiments the graphics core array 1914 also includes executionlogic to perform media functions, such as video and/or image processing.In one embodiment, the execution units additionally includegeneral-purpose logic that is programmable to perform parallel generalpurpose computational operations, in addition to graphics processingoperations. The general-purpose logic can perform processing operationsin parallel or in conjunction with general purpose logic within theprocessor core(s) 1607 of FIG. 16 or core 1702A-1702N as in FIG. 17.

Output data generated by threads executing on the graphics core array1914 can output data to memory in a unified return buffer (URB) 1918.The URB 1918 can store data for multiple threads. In some embodimentsthe URB 1918 may be used to send data between different threadsexecuting on the graphics core array 1914. In some embodiments the URB1918 may additionally be used for synchronization between threads on thegraphics core array and fixed function logic within the shared functionlogic 1920.

In some embodiments, graphics core array 1914 is scalable, such that thearray includes a variable number of graphics cores, each having avariable number of execution units based on the target power andperformance level of GPE 1910. In one embodiment the execution resourcesare dynamically scalable, such that execution resources may be enabledor disabled as needed.

The graphics core array 1914 couples with shared function logic 1920that includes multiple resources that are shared between the graphicscores in the graphics core array. The shared functions within the sharedfunction logic 1920 are hardware logic units that provide specializedsupplemental functionality to the graphics core array 1914. In variousembodiments, shared function logic 1920 includes but is not limited tosampler 1921, math 1922, and inter-thread communication (ITC) 1923logic. Additionally, some embodiments implement one or more cache(s)1925 within the shared function logic 1920. A shared function isimplemented where the demand for a given specialized function isinsufficient for inclusion within the graphics core array 1914. Insteada single instantiation of that specialized function is implemented as astand-alone entity in the shared function logic 1920 and shared amongthe execution resources within the graphics core array 1914. The preciseset of functions that are shared between the graphics core array 1914and included within the graphics core array 1914 varies betweenembodiments.

FIG. 20 is a block diagram of another embodiment of a graphics processor2000. Elements of FIG. 20 having the same reference numbers (or names)as the elements of any other figure herein can operate or function inany manner similar to that described elsewhere herein, but are notlimited to such.

In some embodiments, graphics processor 2000 includes a ringinterconnect 2002, a pipeline front-end 2004, a media engine 2037, andgraphics cores 2080A-2080N. In some embodiments, ring interconnect 2002couples the graphics processor to other processing units, includingother graphics processors or one or more general-purpose processorcores. In some embodiments, the graphics processor is one of manyprocessors integrated within a multi-core processing system.

In some embodiments, graphics processor 2000 receives batches ofcommands via ring interconnect 2002. The incoming commands areinterpreted by a command streamer 2003 in the pipeline front-end 2004.In some embodiments, graphics processor 2000 includes scalable executionlogic to perform 3D geometry processing and media processing via thegraphics core(s) 2080A-2080N. For 3D geometry processing commands,command streamer 2003 supplies commands to geometry pipeline 2036. Forat least some media processing commands, command streamer 2003 suppliesthe commands to a video front-end 2034, which couples with a mediaengine 2037. In some embodiments, media engine 2037 includes a VideoQuality Engine (VQE) 2030 for video and image post-processing and amulti-format encode/decode (MFX) 2033 engine to providehardware-accelerated media data encode and decode. In some embodiments,geometry pipeline 2036 and media engine 2037 each generate executionthreads for the thread execution resources provided by at least onegraphics core 2080A.

In some embodiments, graphics processor 2000 includes scalable threadexecution resources featuring modular cores 2080A-2080N (sometimesreferred to as core slices), each having multiple sub-cores 2050A-550N,2060A-2060N (sometimes referred to as core sub-slices). In someembodiments, graphics processor 2000 can have any number of graphicscores 2080A through 2080N. In some embodiments, graphics processor 2000includes a graphics core 2080A having at least a first sub-core 2050Aand a second sub-core 2060A. In other embodiments, the graphicsprocessor is a low power processor with a single sub-core (e.g., 2050A).In some embodiments, graphics processor 2000 includes multiple graphicscores 2080A-2080N, each including a set of first sub-cores 2050A-2050Nand a set of second sub-cores 2060A-2060N. Each sub-core in the set offirst sub-cores 2050A-2050N includes at least a first set of executionunits 2052A-2052N and media/texture samplers 2054A-2054N. Each sub-corein the set of second sub-cores 2060A-2060N includes at least a secondset of execution units 2062A-2062N and samplers 2064A-2064N. In someembodiments, each sub-core 2050A-2050N, 2060A-2060N shares a set ofshared resources 2070A-2070N. In some embodiments, the shared resourcesinclude shared cache memory and pixel operation logic. Other sharedresources may also be included in the various embodiments of thegraphics processor.

Additional Exemplary Execution Units

FIG. 21 illustrates thread execution logic 2100 including an array ofprocessing elements employed in some embodiments of a GPE. Elements ofFIG. 21 having the same reference numbers (or names) as the elements ofany other figure herein can operate or function in any manner similar tothat described elsewhere herein but are not limited to such.

In some embodiments, thread execution logic 2100 includes a shaderprocessor 2102, a thread dispatcher 2104, instruction cache 2106, ascalable execution unit array including a plurality of execution units2108A-2108N, a sampler 2110, a data cache 2112, and a data port 2114. Inone embodiment the scalable execution unit array can dynamically scaleby enabling or disabling one or more execution units (e.g., any ofexecution unit 2108A, 2108B, 2108C, 2108D, through 2108N-1 and 2108N)based on the computational requirements of a workload. In one embodimentthe included components are interconnected via an interconnect fabricthat links to each of the components. In some embodiments, threadexecution logic 2100 includes one or more connections to memory, such assystem memory or cache memory, through one or more of instruction cache2106, data port 2114, sampler 2110, and execution units 2108A-2108N. Insome embodiments, each execution unit (e.g. 2108A) is a stand-aloneprogrammable general purpose computational unit that is capable ofexecuting multiple simultaneous hardware threads while processingmultiple data elements in parallel for each thread. In variousembodiments, the array of execution units 2108A-2108N is scalable toinclude any number individual execution units.

In some embodiments, the execution units 2108A-2108N are primarily usedto execute shader programs. A shader processor 2102 can process thevarious shader programs and dispatch execution threads associated withthe shader programs via a thread dispatcher 2104. In one embodiment thethread dispatcher includes logic to arbitrate thread initiation requestsfrom the graphics and media pipelines and instantiate the requestedthreads on one or more execution unit in the execution units2108A-2108N. For example, the geometry pipeline (e.g., 2036 of FIG. 20)can dispatch vertex, tessellation, or geometry shaders to the threadexecution logic 2100 of FIG. 21 for processing. In some embodiments,thread dispatcher 2104 can also process runtime thread spawning requestsfrom the executing shader programs.

In some embodiments, the execution units 2108A-2108N support aninstruction set that includes native support for many standard 3Dgraphics shader instructions, such that shader programs from graphicslibraries (e.g., Direct 3D and OpenGL) are executed with a minimaltranslation. The execution units support vertex and geometry processing(e.g., vertex programs, geometry programs, vertex shaders), pixelprocessing (e.g., pixel shaders, fragment shaders) and general-purposeprocessing (e.g., compute and media shaders). Each of the executionunits 2108A-2108N is capable of multi-issue single instruction multipledata (SIMD) execution and multi-threaded operation enables an efficientexecution environment in the face of higher latency memory accesses.Each hardware thread within each execution unit has a dedicatedhigh-bandwidth register file and associated independent thread-state.Execution is multi-issue per clock to pipelines capable of integer,single and double precision floating point operations, SIMD branchcapability, logical operations, transcendental operations, and othermiscellaneous operations. While waiting for data from memory or one ofthe shared functions, dependency logic within the execution units2108A-2108N causes a waiting thread to sleep until the requested datahas been returned. While the waiting thread is sleeping, hardwareresources may be devoted to processing other threads. For example,during a delay associated with a vertex shader operation, an executionunit can perform operations for a pixel shader, fragment shader, oranother type of shader program, including a different vertex shader.

Each execution unit in execution units 2108A-2108N operates on arrays ofdata elements. The number of data elements is the “execution size,” orthe number of channels for the instruction. An execution channel is alogical unit of execution for data element access, masking, and flowcontrol within instructions. The number of channels may be independentof the number of physical Arithmetic Logic Units (ALUs) or FloatingPoint Units (FPUs) for a particular graphics processor. In someembodiments, execution units 2108A-2108N support integer andfloating-point data types.

The execution unit instruction set includes SIMD instructions. Thevarious data elements can be stored as a packed data type in a registerand the execution unit will process the various elements based on thedata size of the elements. For example, when operating on a 256-bit widevector, the 256 bits of the vector are stored in a register and theexecution unit operates on the vector as four separate 64-bit packeddata elements (Quad-Word (QW) size data elements), eight separate 32-bitpacked data elements (Double Word (DW) size data elements), sixteenseparate 16-bit packed data elements (Word (W) size data elements), orthirty-two separate 8-bit data elements (byte (B) size data elements).However, different vector widths and register sizes are possible.

One or more internal instruction caches (e.g., 2106) are included in thethread execution logic 2100 to cache thread instructions for theexecution units. In some embodiments, one or more data caches (e.g.,2112) are included to cache thread data during thread execution. In someembodiments, a sampler 2110 is included to provide texture sampling for3D operations and media sampling for media operations. In someembodiments, sampler 2110 includes specialized texture or media samplingfunctionality to process texture or media data during the samplingprocess before providing the sampled data to an execution unit.

During execution, the graphics and media pipelines send threadinitiation requests to thread execution logic 2100 via thread spawningand dispatch logic. Once a group of geometric objects has been processedand rasterized into pixel data, pixel processor logic (e.g., pixelshader logic, fragment shader logic, etc.) within the shader processor2102 is invoked to further compute output information and cause resultsto be written to output surfaces (e.g., color buffers, depth buffers,stencil buffers, etc.). In some embodiments, a pixel shader or fragmentshader calculates the values of the various vertex attributes that areto be interpolated across the rasterized object. In some embodiments,pixel processor logic within the shader processor 2102 then executes anapplication programming interface (API)-supplied pixel or fragmentshader program. To execute the shader program, the shader processor 2102dispatches threads to an execution unit (e.g., 2108A) via threaddispatcher 2104. In some embodiments, pixel shader 2102 uses texturesampling logic in the sampler 2110 to access texture data in texturemaps stored in memory. Arithmetic operations on the texture data and theinput geometry data compute pixel color data for each geometricfragment, or discards one or more pixels from further processing.

In some embodiments, the data port 2114 provides a memory accessmechanism for the thread execution logic 2100 output processed data tomemory for processing on a graphics processor output pipeline. In someembodiments, the data port 2114 includes or couples to one or more cachememories (e.g., data cache 2112) to cache data for memory access via thedata port.

FIG. 22 is a block diagram illustrating a graphics processor instructionformats 2200 according to some embodiments. In one or more embodiment,the graphics processor execution units support an instruction set havinginstructions in multiple formats. The solid lined boxes illustrate thecomponents that are generally included in an execution unit instruction,while the dashed lines include components that are optional or that areonly included in a sub-set of the instructions. In some embodiments,instruction format 2200 described and illustrated aremacro-instructions, in that they are instructions supplied to theexecution unit, as opposed to micro-operations resulting frominstruction decode once the instruction is processed.

In some embodiments, the graphics processor execution units nativelysupport instructions in a 128-bit instruction format 2210. A 64-bitcompacted instruction format 2230 is available for some instructionsbased on the selected instruction, instruction options, and number ofoperands. The native 128-bit instruction format 710 provides access toall instruction options, while some options and operations arerestricted in the 64-bit format 2230. The native instructions availablein the 64-bit format 2230 vary by embodiment. In some embodiments, theinstruction is compacted in part using a set of index values in an indexfield 2213. The execution unit hardware references a set of compactiontables based on the index values and uses the compaction table outputsto reconstruct a native instruction in the 128-bit instruction format2210.

For each format, instruction opcode 2212 defines the operation that theexecution unit is to perform. The execution units execute eachinstruction in parallel across the multiple data elements of eachoperand. For example, in response to an add instruction the executionunit performs a simultaneous add operation across each color channelrepresenting a texture element or picture element. By default, theexecution unit performs each instruction across all data channels of theoperands. In some embodiments, instruction control field 2214 enablescontrol over certain execution options, such as channels selection(e.g., predication) and data channel order (e.g., swizzle). Forinstructions in the 128-bit instruction format 2210 an exec-size field2216 limits the number of data channels that will be executed inparallel. In some embodiments, exec-size field 2216 is not available foruse in the 64-bit compact instruction format 2230.

Some execution unit instructions have up to three operands including twosource operands, src0 2220, src1 2222, and one destination 2218. In someembodiments, the execution units support dual destination instructions,where one of the destinations is implied. Data manipulation instructionscan have a third source operand (e.g., SRC2 2224), where the instructionopcode 2212 determines the number of source operands. An instruction'slast source operand can be an immediate (e.g., hard-coded) value passedwith the instruction.

In some embodiments, the 128-bit instruction format 2210 includes anaccess/address mode field 2226 specifying, for example, whether directregister addressing mode or indirect register addressing mode is used.When direct register addressing mode is used, the register address ofone or more operands is directly provided by bits in the instruction.

In some embodiments, the 128-bit instruction format 2210 includes anaccess/address mode field 2226, which specifies an address mode and/oran access mode for the instruction. In one embodiment the access mode isused to define a data access alignment for the instruction. Someembodiments support access modes including a 16-byte aligned access modeand a 1-byte aligned access mode, where the byte alignment of the accessmode determines the access alignment of the instruction operands. Forexample, when in a first mode, the instruction may use byte-alignedaddressing for source and destination operands and when in a secondmode, the instruction may use 16-byte-aligned addressing for all sourceand destination operands.

In one embodiment, the address mode portion of the access/address modefield 2226 determines whether the instruction is to use direct orindirect addressing. When direct register addressing mode is used bitsin the instruction directly provide the register address of one or moreoperands. When indirect register addressing mode is used, the registeraddress of one or more operands may be computed based on an addressregister value and an address immediate field in the instruction.

In some embodiment's instructions are grouped based on opcode 2212bit-fields to simplify Opcode decode 2240. For an 8-bit opcode, bits 4,5, and 6 allow the execution unit to determine the type of opcode. Theprecise opcode grouping shown is merely an example. In some embodiments,a move and logic opcode group 2242 includes data movement and logicinstructions (e.g., move (mov), compare (cmp)). In some embodiments,move and logic group 2242 shares the five most significant bits (MSB),where move (mov) instructions are in the form of 0000xxxxb and logicinstructions are in the form of 0001xxxxb. A flow control instructiongroup 2244 (e.g., call, jump (jmp)) includes instructions in the form of0010xxxxb (e.g., 0x20). A miscellaneous instruction group 2246 includesa mix of instructions, including synchronization instructions (e.g.,wait, send) in the form of 0011xxxxb (e.g., 0x30). A parallel mathinstruction group 2248 includes component-wise arithmetic instructions(e.g., add, multiply (mul)) in the form of 0100xxxxb (e.g., 0x40). Theparallel math group 2248 performs the arithmetic operations in parallelacross data channels. The vector math group 2250 includes arithmeticinstructions (e.g., dp4) in the form of 0101xxxxb (e.g., 0x50). Thevector math group performs arithmetic such as dot product calculationson vector operands.

Exemplary Additional Graphics Pipeline

FIG. 23 is a block diagram of another embodiment of a graphics processor2300.

Elements of FIG. 23 having the same reference numbers (or names) as theelements of any other figure herein can operate or function in anymanner similar to that described elsewhere herein, but are not limitedto such.

In some embodiments, graphics processor 2300 includes a graphicspipeline 2320, a media pipeline 2330, a display engine 2340, threadexecution logic 2350, and a render output pipeline 2370. In someembodiments, graphics processor 2300 is a graphics processor within amulti-core processing system that includes one or more general purposeprocessing cores. The graphics processor is controlled by registerwrites to one or more control registers (not shown) or via commandsissued to graphics processor 2300 via a ring interconnect 2302. In someembodiments, ring interconnect 2302 couples graphics processor 2300 toother processing components, such as other graphics processors orgeneral-purpose processors. Commands from ring interconnect 2302 areinterpreted by a command streamer 2303, which supplies instructions toindividual components of graphics pipeline 2320 or media pipeline 2330.

In some embodiments, command streamer 2303 directs the operation of avertex fetcher 2305 that reads vertex data from memory and executesvertex-processing commands provided by command streamer 2303. In someembodiments, vertex fetcher 2305 provides vertex data to a vertex shader2307, which performs coordinate space transformation and lightingoperations to each vertex. In some embodiments, vertex fetcher 2305 andvertex shader 2307 execute vertex-processing instructions by dispatchingexecution threads to execution units 2352A-2352B via a thread dispatcher2331.

In some embodiments, execution units 2352A-2352B are an array of vectorprocessors having an instruction set for performing graphics and mediaoperations. In some embodiments, execution units 2352A-2352B have anattached L1 cache 2351 that is specific for each array or shared betweenthe arrays. The cache can be configured as a data cache, an instructioncache, or a single cache that is partitioned to contain data andinstructions in different partitions.

In some embodiments, graphics pipeline 2320 includes tessellationcomponents to perform hardware-accelerated tessellation of 3D objects.In some embodiments, a programmable hull shader 2311 configures thetessellation operations. A programmable domain shader 2317 providesback-end evaluation of tessellation output. A tessellator 2313 operatesat the direction of hull shader 2311 and contains special purpose logicto generate a set of detailed geometric objects based on a coarsegeometric model that is provided as input to graphics pipeline 2320. Insome embodiments, if tessellation is not used, tessellation components(e.g., hull shader 2311, tessellator 2313, and domain shader 2317) canbe bypassed.

In some embodiments, complete geometric objects can be processed by ageometry shader 2319 via one or more threads dispatched to executionunits 2352A-2352B, or can proceed directly to the clipper 2329. In someembodiments, the geometry shader operates on entire geometric objects,rather than vertices or patches of vertices as in previous stages of thegraphics pipeline. If the tessellation is disabled the geometry shader2319 receives input from the vertex shader 2307. In some embodiments,geometry shader 2319 is programmable by a geometry shader program toperform geometry tessellation if the tessellation units are disabled.Before rasterization, a clipper 2329 processes vertex data. The clipper2329 may be a fixed function clipper or a programmable clipper havingclipping and geometry shader functions. In some embodiments, arasterizer and depth test component 2373 in the render output pipeline2370 dispatches pixel shaders to convert the geometric objects intotheir per pixel representations. In some embodiments, pixel shader logicis included in thread execution logic 2350. In some embodiments, anapplication can bypass the rasterizer and depth test component 2373 andaccess un-rasterized vertex data via a stream out unit 2323.

The graphics processor 2300 has an interconnect bus, interconnectfabric, or some other interconnect mechanism that allows data andmessage passing amongst the major components of the processor. In someembodiments, execution units 2352A-2352B and associated cache(s) 2351,texture and media sampler 2354, and texture/sampler cache 2358interconnect via a data port 2356 to perform memory access andcommunicate with render output pipeline components of the processor. Insome embodiments, sampler 2354, caches 2351, 2358 and execution units2352A-2352B each have separate memory access paths.

In some embodiments, render output pipeline 2370 contains a rasterizerand depth test component 2373 that converts vertex-based objects into anassociated pixel-based representation. In some embodiments, therasterizer logic includes a windower/masker unit to perform fixedfunction triangle and line rasterization. An associated render cache2378 and depth cache 2379 are also available in some embodiments. Apixel operations component 2377 performs pixel-based operations on thedata, though in some instances, pixel operations associated with 2Doperations (e.g. bit block image transfers with blending) are performedby the 2D engine 2341 or substituted at display time by the displaycontroller 2343 using overlay display planes. In some embodiments, ashared L3 cache 2375 is available to all graphics components, allowingthe sharing of data without the use of main system memory.

In some embodiments, graphics processor media pipeline 2330 includes amedia engine 2337 and a video front-end 2334. In some embodiments, videofront-end 2334 receives pipeline commands from the command streamer2303. In some embodiments, media pipeline 2330 includes a separatecommand streamer. In some embodiments, video front-end 2334 processesmedia commands before sending the command to the media engine 2337. Insome embodiments, media engine 2337 includes thread spawningfunctionality to spawn threads for dispatch to thread execution logic2350 via thread dispatcher 2331.

In some embodiments, graphics processor 2300 includes a display engine2340. In some embodiments, display engine 2340 is external to processor2300 and couples with the graphics processor via the ring interconnect2302, or some other interconnect bus or fabric. In some embodiments,display engine 2340 includes a 2D engine 2341 and a display controller2343. In some embodiments, display engine 2340 contains special purposelogic capable of operating independently of the 3D pipeline. In someembodiments, display controller 2343 couples with a display device (notshown), which may be a system integrated display device, as in a laptopcomputer, or an external display device attached via a display deviceconnector.

In some embodiments, graphics pipeline 2320 and media pipeline 2330 areconfigurable to perform operations based on multiple graphics and mediaprogramming interfaces and are not specific to any one applicationprogramming interface (API). In some embodiments, driver software forthe graphics processor translates API calls that are specific to aparticular graphics or media library into commands that can be processedby the graphics processor. In some embodiments, support is provided forthe Open Graphics Library (OpenGL), Open Computing Language (OpenCL),and/or Vulkan graphics and compute API, all from the Khronos Group. Insome embodiments, support may also be provided for the Direct3D libraryfrom the Microsoft Corporation. In some embodiments, a combination ofthese libraries may be supported. Support may also be provided for theOpen Source Computer Vision Library (OpenCV). A future API with acompatible 3D pipeline would also be supported if a mapping can be madefrom the pipeline of the future API to the pipeline of the graphicsprocessor.

Exemplary Graphics Pipeline Programming

FIG. 24A is a block diagram illustrating a graphics processor commandformat 2400 according to some embodiments. FIG. 24B is a block diagramillustrating a graphics processor command sequence 2410 according to anembodiment. The solid lined boxes in FIG. 24A illustrate the componentsthat are generally included in a graphics command while the dashed linesinclude components that are optional or that are only included in asub-set of the graphics commands. The exemplary graphics processorcommand format 2400 of FIG. 24A includes data fields to identify atarget client 2402 of the command, a command operation code (opcode)2404, and the relevant data 2406 for the command. A sub-opcode 2405 anda command size 2408 are also included in some commands.

In some embodiments, client 2402 specifies the client unit of thegraphics device that processes the command data. In some embodiments, agraphics processor command parser examines the client field of eachcommand to condition the further processing of the command and route thecommand data to the appropriate client unit. In some embodiments, thegraphics processor client units include a memory interface unit, arender unit, a 2D unit, a 3D unit, and a media unit. Each client unithas a corresponding processing pipeline that processes the commands.Once the command is received by the client unit, the client unit readsthe opcode 2404 and, if present, sub-opcode 2405 to determine theoperation to perform. The client unit performs the command usinginformation in data field 2406. For some commands an explicit commandsize 2408 is expected to specify the size of the command. In someembodiments, the command parser automatically determines the size of atleast some of the commands based on the command opcode. In someembodiment's commands are aligned via multiples of a double word.

The flow diagram in FIG. 24B shows an exemplary graphics processorcommand sequence 2410. In some embodiments, software or firmware of adata processing system that features an embodiment of a graphicsprocessor uses a version of the command sequence shown to set up,execute, and terminate a set of graphics operations. A sample commandsequence is shown and described for purposes of example only asembodiments are not limited to these specific commands or to thiscommand sequence. Moreover, the commands may be issued as batch ofcommands in a command sequence, such that the graphics processor willprocess the sequence of commands in at least partially concurrence.

In some embodiments, the graphics processor command sequence 2410 maybegin with a pipeline flush command 2412 to cause any active graphicspipeline to complete the currently pending commands for the pipeline. Insome embodiments, the 3D pipeline 2422 and the media pipeline 2424 donot operate concurrently. The pipeline flush is performed to cause theactive graphics pipeline to complete any pending commands. In responseto a pipeline flush, the command parser for the graphics processor willpause command processing until the active drawing engines completepending operations and the relevant read caches are invalidated.Optionally, any data in the render cache that is marked ‘dirty’ can beflushed to memory. In some embodiments, pipeline flush command 2412 canbe used for pipeline synchronization or before placing the graphicsprocessor into a low power state.

In some embodiments, a pipeline select command 2413 is used when acommand sequence requires the graphics processor to explicitly switchbetween pipelines. In some embodiments, a pipeline select command 2413is required only once within an execution context before issuingpipeline commands unless the context is to issue commands for bothpipelines. In some embodiments, a pipeline flush command 2412 isrequired immediately before a pipeline switch via the pipeline selectcommand 2413.

In some embodiments, a pipeline control command 2414 configures agraphics pipeline for operation and is used to program the 3D pipeline2422 and the media pipeline 2424. In some embodiments, pipeline controlcommand 2414 configures the pipeline state for the active pipeline. Inone embodiment, the pipeline control command 2414 is used for pipelinesynchronization and to clear data from one or more cache memories withinthe active pipeline before processing a batch of commands.

In some embodiments, return buffer state commands 2416 are used toconfigure a set of return buffers for the respective pipelines to writedata. Some pipeline operations require the allocation, selection, orconfiguration of one or more return buffers into which the operationswrite intermediate data during processing. In some embodiments, thegraphics processor also uses one or more return buffers to store outputdata and to perform cross thread communication. In some embodiments, thereturn buffer state 2416 includes selecting the size and number ofreturn buffers to use for a set of pipeline operations.

The remaining commands in the command sequence differ based on theactive pipeline for operations. Based on a pipeline determination 2420,the command sequence is tailored to the 3D pipeline 2422 beginning withthe 3D pipeline state 2430 or the media pipeline 2424 beginning at themedia pipeline state 2440.

The commands to configure the 3D pipeline state 2430 include 3D statesetting commands for vertex buffer state, vertex element state, constantcolor state, depth buffer state, and other state variables that are tobe configured before 3D primitive commands are processed. The values ofthese commands are determined at least in part based on the particular3D API in use. In some embodiments, 3D pipeline state 2430 commands arealso able to selectively disable or bypass certain pipeline elements ifthose elements will not be used.

In some embodiments, 3D primitive 2432 command is used to submit 3Dprimitives to be processed by the 3D pipeline. Commands and associatedparameters that are passed to the graphics processor via the 3Dprimitive 2432 command are forwarded to the vertex fetch function in thegraphics pipeline. The vertex fetch function uses the 3D primitive 2432command data to generate vertex data structures. The vertex datastructures are stored in one or more return buffers. In someembodiments, 3D primitive 2432 command is used to perform vertexoperations on 3D primitives via vertex shaders. To process vertexshaders, 3D pipeline 2422 dispatches shader execution threads tographics processor execution units.

In some embodiments, 3D pipeline 2422 is triggered via an execute 2434command or event. In some embodiments, command execution is triggeredvia a register write. In some embodiment's execution is triggered via a‘go’ or ‘kick’ command in the command sequence. In one embodiment,command execution is triggered using a pipeline synchronization commandto flush the command sequence through the graphics pipeline. The 3Dpipeline will perform geometry processing for the 3D primitives. Onceoperations are complete, the resulting geometric objects are rasterizedand the pixel engine colors the resulting pixels. Additional commands tocontrol pixel shading and pixel back end operations may also be includedfor those operations.

In some embodiments, the graphics processor command sequence 2410follows the media pipeline 2424 path when performing media operations.In general, the specific use and manner of programming for the mediapipeline 2424 depends on the media or compute operations to beperformed. Specific media decode operations may be offloaded to themedia pipeline during media decode. In some embodiments, the mediapipeline can also be bypassed and media decode can be performed in wholeor in part using resources provided by one or more general purposeprocessing cores. In one embodiment, the media pipeline also includeselements for general-purpose graphics processor unit (GPGPU) operations,where the graphics processor is used to perform SIMD vector operationsusing computational shader programs that are not explicitly related tothe rendering of graphics primitives.

In some embodiments, media pipeline 2424 is configured in a similarmanner as the 3D pipeline 2422. A set of commands to configure the mediapipeline state 2440 are dispatched or placed into a command queue beforethe media object commands 2442. In some embodiments, commands for themedia pipeline state 2440 include data to configure the media pipelineelements that will be used to process the media objects. This includesdata to configure the video decode and video encode logic within themedia pipeline, such as encode or decode format. In some embodiments,commands for the media pipeline state 2440 also support the use of oneor more pointers to “indirect” state elements that contain a batch ofstate settings.

In some embodiments, media object commands 2442 supply pointers to mediaobjects for processing by the media pipeline. The media objects includememory buffers containing video data to be processed. In someembodiments, all media pipeline states must be valid before issuing amedia object command 2442. Once the pipeline state is configured andmedia object commands 2442 are queued, the media pipeline 2424 istriggered via an execute command 2444 or an equivalent execute event(e.g., register write). Output from media pipeline 2424 may then be postprocessed by operations provided by the 3D pipeline 2422 or the mediapipeline 2424. In some embodiments, GPGPU operations are configured andexecuted in a similar manner as media operations.

Additional Exemplary Graphics Software Architecture

FIG. 25 illustrates exemplary graphics software architecture for a dataprocessing system 2500 according to some embodiments. In someembodiments, software architecture includes a 3D graphics application2510, an operating system 2520, and at least one processor 2530. In someembodiments, processor 2530 includes a graphics processor 2532 and oneor more general-purpose processor core(s) 2534. The graphics application2510 and operating system 2520 each execute in the system memory 2550 ofthe data processing system.

In some embodiments, 3D graphics application 2510 contains one or moreshader programs including shader instructions 2512. The shader languageinstructions may be in a high-level shader language, such as the HighLevel Shader Language (HLSL) or the OpenGL Shader Language (GLSL). Theapplication also includes executable instructions 2514 in a machinelanguage suitable for execution by the general-purpose processor core2534. The application also includes graphics objects 2516 defined byvertex data.

In some embodiments, operating system 2520 is a Microsoft® Windows®operating system from the Microsoft Corporation, a proprietary UNIX-likeoperating system, or an open source UNIX-like operating system using avariant of the Linux kernel. The operating system 2520 can support agraphics API 2522 such as the Direct3D API, the OpenGL API, or theVulkan API. When the Direct3D API is in use, the operating system 2520uses a front-end shader compiler 2524 to compile any shader instructions2512 in HLSL into a lower-level shader language. The compilation may bea just-in-time (JIT) compilation or the application can perform shaderpre-compilation. In some embodiments, high-level shaders are compiledinto low-level shaders during the compilation of the 3D graphicsapplication 2510. In some embodiments, the shader instructions 2512 areprovided in an intermediate form, such as a version of the StandardPortable Intermediate Representation (SPIR) used by the Vulkan API.

In some embodiments, user mode graphics driver 2526 contains a back-endshader compiler 2527 to convert the shader instructions 2512 into ahardware specific representation. When the OpenGL API is in use, shaderinstructions 2512 in the GLSL high-level language are passed to a usermode graphics driver 2526 for compilation. In some embodiments, usermode graphics driver 2526 uses operating system kernel mode functions2528 to communicate with a kernel mode graphics driver 2529. In someembodiments, kernel mode graphics driver 2529 communicates with graphicsprocessor 2532 to dispatch commands and instructions.

Exemplary IP Core Implementations

One or more aspects of at least one embodiment may be implemented byrepresentative code stored on a machine-readable medium which representsand/or defines logic within an integrated circuit such as a processor.For example, the machine-readable medium may include instructions whichrepresent various logic within the processor. When read by a machine,the instructions may cause the machine to fabricate the logic to performthe techniques described herein. Such representations, known as “IPcores,” are reusable units of logic for an integrated circuit that maybe stored on a tangible, machine-readable medium as a hardware modelthat describes the structure of the integrated circuit. The hardwaremodel may be supplied to various customers or manufacturing facilities,which load the hardware model on fabrication machines that manufacturethe integrated circuit. The integrated circuit may be fabricated suchthat the circuit performs operations described in association with anyof the embodiments described herein.

FIG. 26 is a block diagram illustrating an IP core development system2600 that may be used to manufacture an integrated circuit to performoperations according to an embodiment. The IP core development system2600 may be used to generate modular, re-usable designs that can beincorporated into a larger design or used to construct an entireintegrated circuit (e.g., an SOC integrated circuit). A design facility2630 can generate a software simulation 2610 of an IP core design in ahigh level programming language (e.g., C/C++). The software simulation2610 can be used to design, test, and verify the behavior of the IP coreusing a simulation model 2612. The simulation model 2612 may includefunctional, behavioral, and/or timing simulations. A register transferlevel (RTL) design 2615 can then be created or synthesized from thesimulation model 2612. The RTL design 2615 is an abstraction of thebehavior of the integrated circuit that models the flow of digitalsignals between hardware registers, including the associated logicperformed using the modeled digital signals. In addition to an RTLdesign 2615, lower-level designs at the logic level or transistor levelmay also be created, designed, or synthesized. Thus, the particulardetails of the initial design and simulation may vary.

The RTL design 2615 or equivalent may be further synthesized by thedesign facility into a hardware model 2620, which may be in a hardwaredescription language (HDL), or some other representation of physicaldesign data. The HDL may be further simulated or tested to verify the IPcore design. The IP core design can be stored for delivery to a 3^(rd)party fabrication facility 2665 using non-volatile memory 2640 (e.g.,hard disk, flash memory, or any non-volatile storage medium).Alternatively, the IP core design may be transmitted (e.g., via theInternet) over a wired connection 2650 or wireless connection 2660. Thefabrication facility 2665 may then fabricate an integrated circuit thatis based at least in part on the IP core design. The fabricatedintegrated circuit can be configured to perform operations in accordancewith at least one embodiment described herein.

Exemplary System on a Chip Integrated Circuit

FIG. 27-29 illustrated exemplary integrated circuits and associatedgraphics processors that may be fabricated using one or more IP cores,according to various embodiments described herein. In addition to whatis illustrated, other logic and circuits may be included, includingadditional graphics processors/cores, peripheral interface controllers,or general purpose processor cores.

FIG. 27 is a block diagram illustrating an exemplary system on a chipintegrated circuit 2700 that may be fabricated using one or more IPcores, according to an embodiment. Exemplary integrated circuit 2700includes one or more application processor(s) 2705 (e.g., CPUs), atleast one graphics processor 2710, and may additionally include an imageprocessor 2715 and/or a video processor 2720, any of which may be amodular IP core from the same or multiple different design facilities.Integrated circuit 2700 includes peripheral or bus logic including a USBcontroller 2725, UART controller 2730, an SPI/SDIO controller 2735, andan I²S/I²C controller 2740. Additionally, the integrated circuit caninclude a display device 2745 coupled to one or more of ahigh-definition multimedia interface (HDMI) controller 2750 and a mobileindustry processor interface (MIPI) display interface 2755. Storage maybe provided by a flash memory subsystem 2760 including flash memory anda flash memory controller. Memory interface may be provided via a memorycontroller 2765 for access to SDRAM or SRAM memory devices. Someintegrated circuits additionally include an embedded security engine2770.

FIG. 28 is a block diagram illustrating an exemplary graphics processor2810 of a system on a chip integrated circuit that may be fabricatedusing one or more IP cores, according to an embodiment. Graphicsprocessor 2810 can be a variant of the graphics processor 2710 of FIG.27. Graphics processor 2810 includes a vertex processor 2805 and one ormore fragment processor(s) 2815A-2815N (e.g., 2815A, 2815B, 2815C,2815D, through 2815N-1, and 2815N). Graphics processor 2810 can executedifferent shader programs via separate logic, such that the vertexprocessor 2805 is optimized to execute operations for vertex shaderprograms, while the one or more fragment processor(s) 2815A-2815Nexecute fragment (e.g., pixel) shading operations for fragment or pixelshader programs. The vertex processor 2805 performs the vertexprocessing stage of the 3D graphics pipeline and generates primitivesand vertex data. The fragment processor(s) 2815A-2815N use the primitiveand vertex data generated by the vertex processor 2805 to produce aframebuffer that is displayed on a display device. In one embodiment,the fragment processor(s) 2815A-2815N are optimized to execute fragmentshader programs as provided for in the OpenGL API, which may be used toperform similar operations as a pixel shader program as provided for inthe Direct 3D API.

Graphics processor 2810 additionally includes one or more memorymanagement units (MMUs) 2820A-2820B, cache(s) 2825A-2825B, and circuitinterconnect(s) 2830A-2830B. The one or more MMU(s) 2820A-2820B providefor virtual to physical address mapping for graphics processor 2810,including for the vertex processor 2805 and/or fragment processor(s)2815A-2815N, which may reference vertex or image/texture data stored inmemory, in addition to vertex or image/texture data stored in the one ormore cache(s) 2825A-2825B. In one embodiment the one or more MMU(s)2820A-2820B may be synchronized with other MMUs within the system,including one or more MMUs associated with the one or more applicationprocessor(s) 2705, image processor 2715, and/or video processor 2720 ofFIG. 27, such that each processor 2705-2720 can participate in a sharedor unified virtual memory system. The one or more circuitinterconnect(s) 2830A-2830B enable graphics processor 2810 to interfacewith other IP cores within the SoC, either via an internal bus of theSoC or via a direct connection, according to embodiments.

FIG. 29 is a block diagram illustrating an additional exemplary graphicsprocessor 2910 of a system on a chip integrated circuit that may befabricated using one or more IP cores, according to an embodiment.Graphics processor 2910 can be a variant of the graphics processor 2710of FIG. 27. Graphics processor 2910 includes the one or more MMU(s)2820A-2820B, caches 2825A-2825B, and circuit interconnects 2830A-2830Bof the integrated circuit 2800 of FIG. 28.

Graphics processor 2910 includes one or more shader core(s) 2915A-2915N(e.g., 2915A, 2915B, 2915C, 2915D, 2915E, 2915F, through 2915N-1, and2915N), which provides for a unified shader core architecture in which asingle core or type or core can execute all types of programmable shadercode, including shader program code to implement vertex shaders,fragment shaders, and/or compute shaders. The exact number of shadercores present can vary among embodiments and implementations.Additionally, graphics processor 2910 includes an inter-core taskmanager 2905, which acts as a thread dispatcher to dispatch executionthreads to one or more shader cores 2915A-2915N and a tiling unit 2918to accelerate tiling operations for tile-based rendering, in whichrendering operations for a scene are subdivided in image space, forexample to exploit local spatial coherence within a scene or to optimizeuse of internal caches.

The following clauses and/or examples pertain to specific embodiments orexamples thereof. Specifics in the examples may be used anywhere in oneor more embodiments. The various features of the different embodimentsor examples may be variously combined with some features included andothers excluded to suit a variety of different applications. Examplesmay include subject matter such as a method, means for performing actsof the method, at least one machine-readable medium includinginstructions that, when performed by a machine cause the machine toperform acts of the method, or of an apparatus or system according toembodiments and examples described herein. Various components can be ameans for performing the operations or functions described.

One embodiment provides for a general-purpose graphics processing unitcomprising multiple processing units and a pipeline manager todistribute a thread group to the multiple processing units, wherein thepipeline manager is to distribute the thread group as multiple threadsub-groups.

One embodiment provides for a method of managing thread execution on ageneral-purpose graphics processing unit (GPGPU), the method comprisinglaunching multiple thread sub-groups of a thread group on a processingunit of the GPGPU; monitoring execution of the multiple threadsub-groups until a thread sub-group is complete; retiring a completedthread sub-group; and launching one or more pending thread sub-groups onthe processing unit after retiring a completed thread sub-group.

One embodiment provides for a data processing system comprising anon-transitory machine-readable medium to store instructions forexecution by one or more processors of the data processing system; and ageneral-purpose graphics processing unit (GPGPU) comprising multipleprocessing units and a pipeline manager to distribute a thread group tothe multiple processing units, wherein the pipeline manager is todistribute the thread group as multiple thread sub-groups.

One embodiment provides for a general-purpose graphics processing unitcomprising multiple processing elements having a single instruction,multiple thread architecture, the multiple processing elements enabledto perform hardware multithreading, wherein execution context forthreads to be executed is maintained on-chip during execution, ascheduler to schedule a warp to the multiple processing elements,wherein the warp is a group of parallel threads, the warp includesmultiple sub-warps, and threads within the warp diverge at sub-warpgranularity, and a logic unit including hardware or firmware logic, thelogic unit to group active threads from the warp for execution on themultiple processing elements.

In a further embodiment, the multiple processing elements are tomaintain per-thread execution state, enable switching between executioncontexts, and are to yield execution at per-thread granularity.Additionally, the scheduler can schedule threads of the warp at sub-warpgranularity. The multiple processing elements can complete a firstsub-warp of threads and execute a second sub-warp of threads after thefirst sub-warp of threads completes. In one embodiment, the multipleprocessing elements and the scheduler are included within a streamingmultiprocessor. The streaming multiprocessor can additionally include adispatch unit to dispatch threads to the multiple processing elementsand a register file to store independent thread state.

One embodiment provides for a method of managing thread execution on ageneral-purpose graphics processing unit, the method comprisingscheduling a warp to multiple processing elements of the general-purposegraphics processing unit, wherein the warp is a group of parallelthreads, the warp includes multiple sub-warps, and threads within thewarp diverge at sub-warp granularity and grouping active threads fromthe warp for execution on the multiple processing elements, the multipleprocessing elements having a single instruction, multiple threadarchitecture, the multiple processing elements enabled to performhardware multithreading, wherein execution context for threads executedby the multiple processing elements is maintained on-chip duringexecution.

One embodiment provides for a data processing system comprising a memoryto store instructions for execution and a general-purpose graphicsprocessing unit. The general-purpose processing unit includes multipleprocessing elements having a single instruction, multiple threadarchitecture, the multiple processing elements enabled to performhardware multithreading, wherein execution context for threads to beexecuted is maintained on-chip during execution. The general-purposeprocessing unit additionally includes a scheduler to schedule a warp tothe multiple processing elements, where the warp is a group of parallelthreads, the warp includes multiple sub-warps and threads within thewarp diverge at sub-warp granularity. The general-purpose processingunit additionally includes a logic unit including hardware or firmwarelogic, the logic unit to group active threads from the warp forexecution on the multiple processing elements.

One embodiment provides for a general purpose graphics processing unitcomprising multiple processing elements having a single instruction,multiple thread (SIMT) architecture, the multiple processing elements toperform hardware multithreading during execution of a plurality ofthread groups. The plurality of thread groups can include one or moresub-groups of threads. A first sub-group can be associated with a firstthread group and a second sub-group can be associated with a secondthread group. When a first thread in the second sub-group has a datadependency upon a first thread in the first sub-group, circuitryincluding hardware or firmware can launch at least the first thread inthe second sub-group to execute in response to satisfaction of the datadependency.

One embodiment provides for a general-purpose graphics processing devicecomprising multiple processing elements and a logic unit to includehardware or firmware logic. The logic unit can launch threads of a firstthread group on the multiple processing elements, where to launch thethreads of the first thread group includes to distribute threads of thefirst thread group as multiple sub-groups. The logic unit canadditionally manage execution of the multiple sub-groups of the firstthread group, retire a first sub-group of the first thread group, groupactive threads for execution on the multiple processing elements, andlaunch a second sub-group of the first thread group, wherein the secondsub-group is to execute concurrently with a third sub-group from asecond thread group.

One embodiment provides an apparatus comprising an interconnect fabriccomprising one or more fabric switches, a plurality of memory interfacescoupled to the interconnect fabric to provide access to a plurality ofmemory devices, an input/output (IO) interface coupled to theinterconnect fabric to provide access to IO devices, an array ofmultiprocessors coupled to the interconnect fabric, scheduling circuitryto distribute a plurality of thread groups across the array ofmultiprocessors, each thread group comprising a plurality of threads andeach thread comprising a plurality of instructions to be executed by atleast one of the multiprocessors, and a first multiprocessor of thearray of multiprocessors to be assigned to process a first thread groupcomprising a first plurality of threads, the first multiprocessorcomprising a plurality of parallel execution circuits. In a furtherembodiment, to process the first thread group, the plurality of parallelexecution circuits are to execute instructions of a first threadsub-group and instructions of a second thread sub-group, the first andsecond thread sub-groups formed based on the first thread group, theplurality of parallel execution circuits are to execute the instructionsof the first thread sub-group to process a first corresponding portionof an input data set to generate a first portion of an output data setand to execute the instructions of the second thread sub-group toprocess a second corresponding portion of the input data set to generatea second portion of the output data set, and the plurality of parallelexecution circuits are to complete execution of the instructions of thefirst thread sub-group prior to executing the instructions of the secondthread sub-group. A further embodiment can provide a system associatedwith the above apparatus. The apparatus can include a memory managementcircuitry to allocate physical memory of the memory devices as systemmemory and can additionally include an input/output memory managementunit (IOMMU) coupled to the interconnect fabric, where the IOMMUincludes a translation buffer to store virtual-to-physical addresstranslations to access the system memory, including the memory devices.

One embodiment provides a method comprising distributing a plurality ofthread groups across an array of multiprocessors, the array ofmultiprocessors coupled to an interconnect fabric comprising one or morefabric switches to couple the array of multiprocessors to a plurality ofmemory devices, wherein each thread group comprises a plurality ofthreads and each thread comprises a plurality of instructions to beexecuted by at least one of the multiprocessors, assigning a firstmultiprocessor of the array of multiprocessors to process a first threadgroup comprising a first plurality of threads, the first multiprocessorcomprising a plurality of parallel execution circuits, and executinginstructions of a first thread sub-group and instructions of a secondthread sub-group by the plurality of parallel execution circuits, thefirst and second thread sub-groups formed based on the first threadgroup. The instructions of the first thread sub-group are executed toprocess a first corresponding portion of an input data set to generate afirst portion of an output data set and the instructions of the secondthread sub-group are executed to process a second corresponding portionof the input data set to generate a second portion of the output dataset, and execution of the instructions of the first thread sub-group isto complete prior to execution of the instructions of the second threadsub-group.

The general purpose graphics processing units above can be coupled to amemory and included on a PCB board to provide a graphics processingsystem in the form of a GPU add-in card coupled to a PCIe or NV-Linkinterface.

One embodiment provides for a method comprising, on a general purposegraphics processing unit having a single instruction, multiple thread(SIMT) architecture, performing hardware multithreading during executionof a plurality of thread groups, at least two of the plurality of threadgroups including one or more sub-groups. A first sub-group can beassociated with a first thread group, a second sub-group can beassociated with a second thread group, and a first thread in the secondsub-group can have a data dependency upon a first thread in the firstsub-group. The method additionally includes launching at least the firstthread in the second sub-group in response to satisfaction of the datadependency.

The embodiments described herein refer to specific configurations ofhardware, such as application specific integrated circuits (ASICs),configured to perform certain operations or having a predeterminedfunctionality. Such electronic devices typically include a set of one ormore processors coupled to one or more other components, such as one ormore storage devices (non-transitory machine-readable storage media),user input/output devices (e.g., a keyboard, a touchscreen, and/or adisplay), and network connections. The coupling of the set of processorsand other components is typically through one or more busses and bridges(also termed as bus controllers). The storage device and signalscarrying the network traffic respectively represent one or moremachine-readable storage media and machine-readable communication media.Thus, the storage devices of a given electronic device typically storecode and/or data for execution on the set of one or more processors ofthat electronic device.

Of course, one or more parts of an embodiment may be implemented usingdifferent combinations of software, firmware, and/or hardware.Throughout this detailed description, for the purposes of explanation,numerous specific details were set forth in order to provide a thoroughunderstanding of the present invention. It will be apparent, however, toone skilled in the art that the embodiments may be practiced withoutsome of these specific details. In certain instances, well-knownstructures and functions were not described in elaborate detail to avoidobscuring the inventive subject matter of the embodiments. Accordingly,the scope and spirit of the invention should be judged in terms of theclaims that follow.

What is claimed is:
 1. An apparatus comprising: an interconnect fabriccomprising one or more fabric switches; a plurality of memory interfacescoupled to the interconnect fabric to provide access to a plurality ofmemory devices; an input/output (IO) interface coupled to theinterconnect fabric to provide access to IO devices; an array ofmultiprocessors coupled to the interconnect fabric; scheduling circuitryto distribute a plurality of thread groups across the array ofmultiprocessors, each thread group comprising a plurality of threads andeach thread comprising a plurality of instructions to be executed by atleast one of the multiprocessors; and a first multiprocessor of thearray of multiprocessors to be assigned to process a first thread groupcomprising a first plurality of threads, the first multiprocessorcomprising a plurality of parallel execution circuits, wherein toprocess the first thread group, the plurality of parallel executioncircuits are to execute instructions of a first thread sub-group andinstructions of a second thread sub-group, the first and second threadsub-groups formed based on the first thread group, wherein the pluralityof parallel execution circuits are to execute the instructions of thefirst thread sub-group to process a first corresponding portion of aninput data set to generate a first portion of an output data set and toexecute the instructions of the second thread sub-group to process asecond corresponding portion of the input data set to generate a secondportion of the output data set, and wherein the plurality of parallelexecution circuits are to complete execution of the instructions of thefirst thread sub-group prior to executing the instructions of the secondthread sub-group.
 2. The apparatus of claim 1 further comprising: threadsub-group identification circuitry to distinguish between threads of thefirst thread sub-group and the second thread sub-group.
 3. The apparatusof claim 2 further comprising: tracking circuitry to track a number ofactive sub-groups of a thread group.
 4. The apparatus of claim 3,wherein the tracking circuitry is additionally configured to track anumber of active threads of each sub-group of the thread group.
 5. Theapparatus of claim 4, further comprising: a dispatcher to dispatch eachthread of the first and second sub-groups of the thread group.
 6. Theapparatus of claim 1 wherein the first thread group comprises 64threads.
 7. The apparatus of claim 1 further comprising: a cachehierarchy to store data for the array of multiprocessors, the cachehierarchy including an L1 cache and an L2 cache, the L2 cache to beshared between two or more of the plurality of multiprocessors.
 8. Theapparatus of claim 1 wherein a separate instance of a first instructionis included in each of the threads in the first thread sub-group andeach of the threads in the second thread sub-group.
 9. The apparatus ofclaim 8 wherein the plurality of parallel execution circuits are toexecute each instance of the first instruction on a different portion ofthe input data set.
 10. The apparatus of claim 1 wherein the firstmultiprocessor of the array of multiprocessors to be assigned to processa second thread group, wherein at least one instruction in the secondthread group comprises a barrier instruction to specify one or moredependencies associated with the second thread group.
 11. The apparatusof claim 1 further comprising: virtualization circuitry to share thearray of multiprocessors with a plurality of virtual machines.
 12. Theapparatus of claim 11 wherein the virtualization circuitry comprisesmultiple sets of control registers to be associated with multiplecorresponding virtual machines, a group of control registers to storeone or more address pointers to identify a region of memory associatedwith a corresponding virtual machine.
 13. The apparatus of claim 1further comprising: memory management circuitry to allocate physicalmemory of the memory devices as system memory.
 14. The apparatus ofclaim 13 further comprising: an input/output memory management unit(IOMMU) coupled to the interconnect fabric, the IOMMU comprising atranslation buffer to store virtual-to-physical address translations toaccess the system memory, including the memory devices.
 15. Theapparatus of claim 14 wherein a first one or more virtual-to-physicaladdress translations are to identify regions in the memory devices andwherein a second one or more virtual-to-physical address translationsare to identify regions in a system memory device.
 16. The apparatus ofclaim 15 wherein the array of multiprocessors are to connect to thesystem memory device via the IO interface.
 17. The apparatus of claim 1further comprising: media processing circuitry to perform video decodingand encoding in accordance with one or more codecs.
 18. The apparatus ofclaim 1 further comprising: compression circuitry to compress depth orcolor data that is written to the memory devices and decompress depth orcolor data that is read from the memory devices.
 19. The apparatus ofclaim 1 further comprising: a primitive assembler coupled to the arrayof multiprocessors, the primitive assembler to assemble triangles basedon vertices of the triangles; and a rasterizer to generate pixels basedon the triangles.
 20. A system comprising: a system memory to storeinstructions; and a processor coupled to the system memory, theprocessor comprising: an interconnect fabric comprising one or morefabric switches; a plurality of memory interfaces coupled to theinterconnect fabric to provide access to a plurality of memory devices;an input/output (IO) interface coupled to the interconnect fabric toprovide access to IO devices; an array of multiprocessors coupled to theinterconnect fabric; scheduling circuitry to distribute a plurality ofthread groups across the array of multiprocessors, each thread groupcomprising a plurality of threads and each thread comprising a pluralityof instructions to be executed by at least one of the multiprocessors;and a first multiprocessor of the array of multiprocessors to beassigned to process a first thread group comprising a first plurality ofthreads, the first multiprocessor comprising a plurality of parallelexecution circuits, wherein to process the first thread group, theplurality of parallel execution circuits are to execute instructions ofa first thread sub-group and instructions of a second thread sub-group,the first and second thread sub-groups formed based on the first threadgroup, wherein the plurality of parallel execution circuits are toexecute the instructions of the first thread sub-group to process afirst corresponding portion of an input data set to generate a firstportion of an output data set and to execute the instructions of thesecond thread sub-group to process a second corresponding portion of theinput data set to generate a second portion of the output data set, andwherein the plurality of parallel execution circuits are to completeexecution of the instructions of the first thread sub-group prior toexecuting the instructions of the second thread sub-group.
 21. Thesystem of claim 20 further comprising: thread sub-group identificationcircuitry to distinguish between threads of the first thread sub-groupand the second thread sub-group.
 22. The system of claim 21 furthercomprising: tracking circuitry to track a number of active sub-groups ofa thread group.
 23. The system of claim 22, wherein the trackingcircuitry is additionally configured to track a number of active threadsof each sub-group of the thread group.
 24. The system of claim 23,further comprising: a dispatcher to dispatch each thread of the firstand second sub-groups of the thread group.
 25. The system of claim 20wherein the first thread group comprises 64 threads.
 26. The system ofclaim 20 further comprising: a cache hierarchy to store data for thearray of multiprocessors, the cache hierarchy including an L1 cache andan L2 cache, the L2 cache to be shared between two or more of theplurality of multiprocessors.
 27. The system of claim 20 wherein aseparate instance of a first instruction is included in each of thethreads in the first thread sub-group and each of the threads in thesecond thread sub-group.
 28. The system of claim 27 wherein theplurality of parallel execution circuits are to execute each instance ofthe first instruction on a different portion of the input data set. 29.The system of claim 20 wherein the first multiprocessor of the array ofmultiprocessors to be assigned to process a second thread group, whereinat least one instruction in the second thread group comprises a barrierinstruction to specify one or more dependencies associated with thesecond thread group.
 30. The system of claim 20 further comprising:virtualization circuitry to share the array of multiprocessors with aplurality of virtual machines.
 31. The system of claim 30 wherein thevirtualization circuitry comprises multiple sets of control registers tobe associated with multiple corresponding virtual machines, a group ofcontrol registers to store one or more address pointers to identify aregion of memory associated with a corresponding virtual machine. 32.The system of claim 20 further comprising: memory management circuitryto allocate physical memory of the memory devices as system memory. 33.The system of claim 32 further comprising: an input/output memorymanagement unit (IOMMU) coupled to the interconnect fabric, the IOMMUcomprising a translation buffer to store virtual-to-physical addresstranslations to access the system memory, including the memory devices.34. The system of claim 33 wherein a first one or morevirtual-to-physical address translations are to identify regions in thememory devices and wherein a second one or more virtual-to-physicaladdress translations are to identify regions in a system memory device.35. The system of claim 34 wherein the array of multiprocessors are toconnect to the system memory device via the IO interface.
 36. The systemof claim 20 further comprising: media processing circuitry to performvideo decoding and encoding in accordance with one or more codecs. 37.The system of claim 20 further comprising: compression circuitry tocompress depth or color data that is written to the memory devices anddecompress depth or color data that is read from the memory devices. 38.The system of claim 20 further comprising: a primitive assembler coupledto the array of multiprocessors, the primitive assembler to assembletriangles based on vertices of the triangle; and a rasterizer togenerate pixels based on the triangles.
 39. The system of claim 20further comprising: an input/output (IO) interconnect coupled to the IOinterface, the IO interconnect to couple the processor to the systemmemory.
 40. The system of claim 39 further comprising: a storage devicecoupled to the processor via the IO interconnect.
 41. The system ofclaim 40 wherein the processor comprises a graphics processor, thesystem further comprising: a host processor coupled to the graphicsprocessor over the IO interconnect.
 42. A method comprising:distributing a plurality of thread groups across an array ofmultiprocessors, the array of multiprocessors coupled to an interconnectfabric comprising one or more fabric switches to couple the array ofmultiprocessors to a plurality of memory devices, wherein each threadgroup comprises a plurality of threads and each thread comprises aplurality of instructions to be executed by at least one of themultiprocessors; and assigning a first multiprocessor of the array ofmultiprocessors to process a first thread group comprising a firstplurality of threads, the first multiprocessor comprising a plurality ofparallel execution circuits; and executing instructions of a firstthread sub-group and instructions of a second thread sub-group by theplurality of parallel execution circuits, the first and second threadsub-groups formed based on the first thread group, wherein theinstructions of the first thread sub-group are executed to process afirst corresponding portion of an input data set to generate a firstportion of an output data set and the instructions of the second threadsub-group are executed to process a second corresponding portion of theinput data set to generate a second portion of the output data set,wherein execution of the instructions of the first thread sub-group isto complete prior to execution of the instructions of the second threadsub-group.
 43. The method of claim 42, further comprising:distinguishing between threads of the first thread sub-group and thesecond thread sub-group by thread sub-group identification circuitry.44. The method of claim 43, further comprising: tracking a number ofactive sub-groups of a thread group.
 45. The method of claim 44, furthercomprising: tracking a number of active threads of each sub-group of thethread group.
 46. The method of claim 45, further comprising:dispatching each thread of the first and second thread sub-groups of thethread group.
 47. The method of claim 42 wherein the first thread groupcomprises 64 threads.
 48. The method of claim 42 wherein a separateinstance of a first instruction is included in each of the threads inthe first thread sub-group and each of the threads in the second threadsub-group.
 49. The method of claim 48 wherein the plurality of parallelexecution circuits are to execute each instance of the first instructionon a different portion of the input data set.
 50. The method of claim 42wherein at least one instruction in the second thread group comprises abarrier instruction to specify one or more dependencies associated withthe second thread group.
 51. The method of claim 42 further comprising:sharing the array of multiprocessors with a plurality of virtualmachines.
 52. The method of claim 42 further comprising: allocatephysical memory of the memory devices to as system memory.
 53. Themethod of claim 52 further comprising: storing virtual-to-physicaladdress translations to access the system memory, including the memorydevices.
 54. The method of claim 53 wherein a first one or morevirtual-to-physical address translations are to identify regions in thememory devices and wherein a second one or more virtual-to-physicaladdress translations are to identify regions in a system memory device.55. The method of claim 42 wherein the first thread group comprisesinstructions for processing graphics data, the method furthercomprising: compressing depth or color data that is written to thememory devices and decompress depth or color data that is read from thememory devices.
 56. The method of claim 55 further comprising:assembling triangles based on vertices of primitives specified in thegraphics data; and generating pixels based on the triangles.
 57. Amachine-readable medium having program code stored thereon which, whenexecuted by a machine, causes the machine to perform operationscomprising: distributing a plurality of thread groups across an array ofmultiprocessors, the array of multiprocessors coupled to an interconnectfabric comprising one or more fabric switches to couple the array ofmultiprocessors to a plurality of memory devices, wherein each threadgroup comprises a plurality of threads and each thread comprises aplurality of instructions to be executed by at least one of themultiprocessors; and assigning a first multiprocessor of the array ofmultiprocessors to process a first thread group comprising a firstplurality of threads, the first multiprocessor comprising a plurality ofparallel execution circuits; and executing instructions of a firstthread sub-group and instructions of a second thread sub-group by theplurality of parallel execution circuits, the first and second threadsub-groups formed based on the first thread group, wherein theinstructions of the first thread sub-group are executed to process afirst corresponding portion of an input data set to generate a firstportion of an output data set and the instructions of the second threadsub-group are executed to process a second corresponding portion of theinput data set to generate a second portion of the output data set, andwherein execution of the instructions of the first thread sub-group isto complete prior to execution of the instructions of the second threadsub-group.
 58. The machine-readable medium of claim 57, furthercomprising program code to cause the machine to perform the operationsof: distinguishing between threads of the first sub-group and the secondthread sub-group by thread sub-group identification circuitry.
 59. Themachine-readable medium of claim 58, further comprising program code tocause the machine to perform the operations of: tracking a number ofactive sub-groups of a thread group.
 60. The machine-readable medium ofclaim 59, further comprising program code to cause the machine toperform the operations of: tracking a number of active threads of eachsub-group of the thread group.
 61. The machine-readable medium of claim60, further comprising program code to cause the machine to perform theoperations of: dispatching each thread of the first and secondsub-groups of the thread group.
 62. The machine-readable medium of claim57 wherein the first thread group comprises 64 threads.
 63. Themachine-readable medium of claim 57 wherein a separate instance of afirst instruction is included in each of the threads in the first threadsub-group and each of the threads in the second thread sub-group. 64.The machine-readable medium of claim 63 wherein the plurality ofparallel execution circuits are to execute each instance of the firstinstruction on a different portion of the input data set.
 65. Themachine-readable medium of claim 57 wherein at least one instruction inthe second thread group comprises a barrier instruction to specify oneor more dependencies associated with the second thread group.
 66. Themachine-readable medium of claim 57 further comprising program code tocause the machine to perform the operations of: sharing the array ofmultiprocessors with a plurality of virtual machines.
 67. Themachine-readable medium of claim 57 further comprising program code tocause the machine to perform the operations of: allocate physical memoryof the memory devices to as system memory.
 68. The machine-readablemedium of claim 67 further comprising program code to cause the machineto perform the operations of: storing virtual-to-physical addresstranslations to access the system memory, including the memory devices.69. The machine-readable medium of claim 68 wherein a first one or morevirtual-to-physical address translations are to identify regions in thememory devices and wherein a second one or more virtual-to-physicaladdress translations are to identify regions in a system memory device.70. The machine-readable medium of claim 57 wherein the first threadgroup comprises instructions for processing graphics data, and theoperations further comprise: compressing depth or color data that iswritten to the memory devices and decompress depth or color data that isread from the memory devices.
 71. The machine-readable medium of claim70 further comprising program code to cause the machine to perform theoperations of: assembling triangles based on vertices of primitivesspecified in the graphics data; and generating pixels based on thetriangles.